13.4.1.1 Other Sparse Coding, Invariants

Chapter Contents (Back)
Sparse Coding. Object Recognition. See also Other, Kernel Methods, Invariants.

Pham, T.V.[Thang V.], and Smeulders, A.W.M.[Arnold W.M.],
Sparse Representation for Coarse and Fine Object Recognition,
PAMI(28), No. 4, April 2006, pp. 555-567.
IEEE DOI 0604
Object appearence using a dictionary of Gaussian differential basis functions. Adding new objects does not require retraining old objects. BibRef

Feng, J., Ni, B., Xu, D., Yan, S.,
Histogram Contextualization,
IP(21), No. 2, February 2012, pp. 778-788.
IEEE DOI 1201
Histogram loses the order. Technique to incoprorate spatial information. BibRef

Lui, Y.M.[Yui Man],
Advances in matrix manifolds for computer vision,
IVC(30), No. 6-7, June 2012, pp. 380-388.
Elsevier DOI 1206
Lie groups; Stiefel manifolds; Grassmann manifolds; Riemannian manifolds BibRef

Wang, J., Gong, Y.,
Discovering Image Semantics in Codebook Derivative Space,
MultMed(14), No. 4, 2012, pp. 986-994.
IEEE DOI 1208
Sparse coding. Locality-constraint linear coding. BibRef

Jing, L., Zhang, C., Ng, M.K.,
SNMFCA: Supervised NMF-Based Image Classification and Annotation,
IP(21), No. 11, November 2012, pp. 4508-4521.
IEEE DOI 1210
nonnegative matrix factorization. Classification and annotation. BibRef

Chen, X.[Xi], Zhang, J.S.[Jia-Shu], Li, D.F.[De-Fang],
Direct Discriminant Locality Preserving Projection With Hammerstein Polynomial Expansion,
IP(21), No. 12, December 2012, pp. 4858-4867.
IEEE DOI 1212
BibRef

Li, Q., Zhang, H., Guo, J., Bhanu, B., An, L.,
Reference-Based Scheme Combined With K-SVD for Scene Image Categorization,
SPLetters(20), No. 1, January 2013, pp. 67-70.
IEEE DOI 1212
Locality-constrained Linear Coding (LLC) features BibRef

Li, Q.[Qun], Xu, D.[Ding], An, L.[Le],
Discriminative Reference-Based Scene Image Categorization,
IEICE(E97-D), No. 10, October 2014, pp. 2823-2826.
WWW Link. 1411
BibRef

Duan, C.H.[Chih-Hsueh], Chiang, C.K.[Chen-Kuo], Lai, S.H.[Shang-Hong],
Face Verification With Local Sparse Representation,
SPLetters(20), No. 2, February 2013, pp. 177-180.
IEEE DOI 1302
BibRef

Chiang, C.K.[Chen-Kuo], Liu, C.H.[Chao-Hsien], Duan, C.H.[Chih-Hsueh], Lai, S.H.[Shang-Hong],
Learning Component-Level Sparse Representation for Image and Video Categorization,
IP(22), No. 12, 2013, pp. 4775-4787.
IEEE DOI 1312
image classification BibRef

Irie, G.[Go], Li, Z.G.[Zhen-Guo], Wu, X.M.[Xiao-Ming], Chang, S.F.[Shih-Fu],
Locally Linear Hashing for Extracting Non-linear Manifolds,
CVPR14(2123-2130)
IEEE DOI 1409
hashing; local linearity; manifold; retrieval BibRef

Chiang, C.K.[Chen-Kuo], Duan, C.H.[Chih-Hsueh], Lai, S.H.[Shang-Hong], Chang, S.F.[Shih-Fu],
Learning component-level sparse representation using histogram information for image classification,
ICCV11(1519-1526).
IEEE DOI 1201
Image group statistics. Select the dictionary to best reconstruct the data. BibRef

Tang, J.H.[Jin-Hui], Yan, S.C.[Shui-Cheng], Wright, J.[John], Tian, Q.[Qi], Pang, Y.W.[Yan-Wei], Pissaloux, E.[Edwige],
Sparse representations for image and video analysis,
JVCIR(24), No. 2, February 2013, pp. 93-94.
Elsevier DOI 1302
BibRef

Ricci, E.[Elisa], Zen, G.[Gloria], Sebe, N.[Nicu], Messelodi, S.,
A Prototype Learning Framework Using EMD: Application to Complex Scenes Analysis,
PAMI(35), No. 3, March 2013, pp. 513-526.
IEEE DOI 1303
BibRef

Zen, G.[Gloria], Ricci, E.[Elisa], Sebe, N.[Nicu],
Exploiting Sparse Representations for Robust Analysis of Noisy Complex Video Scenes,
ECCV12(VI: 199-213).
Springer DOI 1210
BibRef

Zen, G.[Gloria], Rostamzadeh, N.[Negar], Staiano, J.[Jacopo], Ricci, E.[Elisa], Sebe, N.[Nicu],
Enhanced semantic descriptors for functional scene categorization,
ICPR12(1985-1988).
WWW Link. 1302
BibRef

Liu, B.D.[Bao-Di], Wang, Y.X.[Yu-Xiong], Zhang, Y.J.[Yu-Jin], Shen, B.[Bin],
Learning dictionary on manifolds for image classification,
PR(46), No. 7, July 2013, pp. 1879-1890.
Elsevier DOI 1303
Sparse coding; Image classification; Locally linear embedding; Coordinate descent; Manifold BibRef

Ravishankar, S.[Saiprasad], Bresler, Y.[Yoram],
Learning Doubly Sparse Transforms for Images,
IP(22), No. 12, 2013, pp. 4598-4612.
IEEE DOI 1312
BibRef
Earlier:
Learning sparsifying transforms for image processing,
ICIP12(681-684).
IEEE DOI 1302
BibRef
And:
Learning doubly sparse transforms for image representation,
ICIP12(685-688).
IEEE DOI 1302
image denoising BibRef

Lu, C.[Cewu], Shi, J.P.[Jian-Ping], Jia, J.Y.[Jia-Ya],
Scale Adaptive Dictionary Learning,
IP(23), No. 2, February 2014, pp. 837-847.
IEEE DOI 1402
BibRef
Earlier:
Online Robust Dictionary Learning,
CVPR13(415-422)
IEEE DOI 1309
image reconstruction. Dictionary Learning; Online Learning; Robust Statistics BibRef

Nozari, H.[Hani], Karami, M.R.[Mohammad Reza],
Design redundant Chebyshev dictionary with generalized extreme value distribution for sparse approximation and image denoising,
SIViP(8), No. 2, February 2014, pp. 327-338.
Springer DOI 1402
Sparse coding. BibRef

Berthoumieu, Y., Dossal, C., Pustelnik, N., Ricoux, P., Turcu, F.,
An Evaluation of the Sparsity Degree for Sparse Recovery with Deterministic Measurement Matrices,
JMIV(48), No. 2, February 2014, pp. 266-278.
Springer DOI 1402
BibRef

Chen, Y.J.[Yun-Jin], Ranftl, R.[Rene], Pock, T.[Thomas],
Insights Into Analysis Operator Learning: From Patch-Based Sparse Models to Higher Order MRFs,
IP(23), No. 3, March 2014, pp. 1060-1072.
IEEE DOI 1403
image denoising BibRef

Bako, L.,
Subspace Clustering Through Parametric Representation and Sparse Optimization,
SPLetters(21), No. 3, March 2014, pp. 356-360.
IEEE DOI 1403
convex programming BibRef

Park, S.[Soonyong], Park, S.K.[Sung-Kee], Hebert, M.,
Fast and Scalable Approximate Spectral Matching for Higher Order Graph Matching,
PAMI(36), No. 3, March 2014, pp. 479-492.
IEEE DOI 1403
approximation theory. approximated affinity tensor. BibRef

Zhang, C.J.[Chun-Jie], Liu, J.[Jing], Liang, C.[Chao], Xue, Z.[Zhe], Pang, J.B.[Jun-Biao], Huang, Q.M.[Qing-Ming],
Image classification by non-negative sparse coding, correlation constrained low-rank and sparse decomposition,
CVIU(123), No. 1, 2014, pp. 14-22.
Elsevier DOI 1405
Sparse coding BibRef

Zhang, C.J.[Chun-Jie], Liu, J.[Jing], Tian, Q.[Qi], Xu, C.S.[Chang-Sheng], Lu, H.Q.[Han-Qing], Ma, S.D.[Song-De],
Image classification by non-negative sparse coding, low-rank and sparse decomposition,
CVPR11(1673-1680).
IEEE DOI 1106
BibRef

Zhang, T.Z.[Tian-Zhu], Ghanem, B.[Bernard], Liu, S.[Si], Xu, C.S.[Chang-Sheng], Ahuja, N.[Narendra],
Low-Rank Sparse Coding for Image Classification,
ICCV13(281-288)
IEEE DOI 1403
bow; image classification; low-rank See also Robust Visual Tracking Via Consistent Low-Rank Sparse Learning. BibRef

Somasundaram, G.[Guruprasad], Cherian, A.[Anoop], Morellas, V.[Vassilios], Papanikolopoulos, N.[Nikolaos],
Action recognition using global spatio-temporal features derived from sparse representations,
CVIU(123), No. 1, 2014, pp. 1-13.
Elsevier DOI 1405
BibRef
Earlier: A1, A3, A4, Only:
Object classification with efficient global self-similarity descriptors based on sparse representations,
ICIP12(2165-2168).
IEEE DOI 1302
BibRef
And: A2, A3, A4, Only:
Robust Sparse Hashing,
ICIP12(2417-2420).
IEEE DOI 1302
Global spatio-temporal features BibRef

Cherian, A.[Anoop], Sra, S.[Suvrit], Morellas, V.[Vassilios], Papanikolopoulos, N.P.[Nikolaos P.],
Efficient Nearest Neighbors via Robust Sparse Hashing,
IP(23), No. 8, August 2014, pp. 3646-3655.
IEEE DOI 1408
cryptography See also Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices. BibRef

Zheng, N.[Ning], Qi, L.[Lin], Guan, L.[Ling],
Generalized multiple maximum scatter difference feature extraction using QR decomposition,
JVCIR(25), No. 6, 2014, pp. 1460-1471.
Elsevier DOI 1407
Feature extraction BibRef

Zheng, N.[Ning], Qi, L.[Lin], Gao, L.[Lei], Guan, L.[Ling],
Generalized MMSD feature extraction using QR decomposition,
VCIP12(1-5).
IEEE DOI 1302
Multiple Maximum scatter difference. BibRef

Yang, W.K.[Wan-Kou], Wang, Z.Y.[Zhen-Yu], Sun, C.Y.[Chang-Yin],
A collaborative representation based projections method for feature extraction,
PR(48), No. 1, 2015, pp. 20-27.
Elsevier DOI 1410
Sparse representation BibRef

Jiang, R., Qiao, H., Zhang, B.,
Speeding Up Graph Regularized Sparse Coding by Dual Gradient Ascent,
SPLetters(22), No. 3, March 2015, pp. 313-317.
IEEE DOI 1410
Convergence BibRef

Su, Y.[Ya], Li, S., Wang, S.J.[Sheng-Jin], Fu, Y.[Yun],
Submanifold Decomposition,
CirSysVideo(24), No. 11, November 2014, pp. 1885-1897.
IEEE DOI 1411
BibRef
Earlier: A1, A3, A4, Only:
Submanifold decomposition,
ICPR12(1755-1758).
WWW Link. 1302
BibRef

Liu, Y.[Yang], Liu, C.[Chenyu], Tang, Y.[Yufang], Liu, H.[Haixu], Ouyang, S.X.[Shu-Xin], Li, X.M.[Xue-Ming],
Robust block sparse discriminative classification framework,
JOSA-A(31), No. 12, December 2014, pp. 2806-2813.
DOI Link 1412
Image processing; Pattern recognition; Machine vision; Algorithms Apply to texture and face recognition. BibRef

Liu, Y.[Yang], Li, X.M.[Xue-Ming], Liu, C.[Chenyu], Liu, H.[Haixu],
Structure-Constrained Low-Rank and Partial Sparse Representation with Sample Selection for image classification,
PR(59), No. 1, 2016, pp. 5-13.
Elsevier DOI 1609
BibRef
Earlier: A1, A4, A3, A2:
Structure-constrained low-rank and partial sparse representation for image classification,
ICIP14(5222-5226)
IEEE DOI 1502
Sparse coding Accuracy BibRef

Xu, Y.[Yi], Yu, L.C.[Li-Cheng], Xu, H.T.[Hong-Teng], Zhang, H.[Hao], Nguyen, T.[Truong],
Vector Sparse Representation of Color Image Using Quaternion Matrix Analysis,
IP(24), No. 4, April 2015, pp. 1315-1329.
IEEE DOI 1503
channel coding BibRef

Shen, X.Y.[Xin-Yue], Gu, Y.T.[Yuan-Tao],
Restricted Isometry Property of Subspace Projection Matrix Under Random Compression,
SPLetters(22), No. 9, September 2015, pp. 1326-1330.
IEEE DOI 1503
matrix algebra BibRef

Patel, J.N.[Jigisha N.], Jose, J.[Jerin], Patnaik, S.[Suprava],
Application of Content Specific Dictionaries in Still Image Coding,
IEICE(E98-D), No. 1, February 2015, pp. 394-403.
WWW Link. 1503
For coding, compression. BibRef

Zhou, X.W.[Xiao-Wei], Yang, C.[Can], Zhao, H.Y.[Hong-Yu], Yu, W.C.[Wei-Chuan],
Low-Rank Modeling and Its Applications in Image Analysis,
Surveys(47), No. 2, January 2015, pp. Article No 36.
DOI Link 1503
Low-rank modeling generally refers to a class of methods that solves problems by representing variables of interest as low-rank matrices. It has achieved great success in various fields including computer vision, data mining, signal processing, and bioinformatics. BibRef

Srinivas, U.[Umamahesh], Suo, Y.M.[Yuan-Ming], Dao, M.[Minh], Monga, V.[Vishal], Tran, T.D.[Trac D.],
Structured Sparse Priors for Image Classification,
IP(24), No. 6, June 2015, pp. 1763-1776.
IEEE DOI 1504
BibRef
Earlier: ICIP13(3211-3215)
IEEE DOI 1402
Class-specific priors Algorithm design and analysis. BibRef

Mousavi, H.S., Monga, V., Tran, T.D.,
Iterative Convex Refinement for Sparse Recovery,
SPLetters(22), No. 11, November 2015, pp. 1903-1907.
IEEE DOI 1509
Bayes methods BibRef

Suo, Y.M.[Yuan-Ming], Dao, M.[Minh], Tran, T.D.[Trac D.], Mousavi, H.S.[Hojjat S.], Srinivas, U.[Umamahesh], Monga, V.[Vishal],
Group structured dirty dictionary learning for classification,
ICIP14(150-154)
IEEE DOI 1502
Dictionaries BibRef

Mousavi, H.S.[Hojjat S.], Srinivas, U.[Umamahesh], Monga, V.[Vishal], Suo, Y.M.[Yuan-Ming], Dao, M.[Minh], Tran, T.D.[Trac D.],
Multi-task image classification via collaborative, hierarchical spike-and-slab priors,
ICIP14(4236-4240)
IEEE DOI 1502
Bayes methods BibRef

Zhi, R.C.[Rui-Cong], Zhao, L.[Lei], Shi, B.[Bolin], Jin, Y.[Yi],
Learning a Two-Dimensional Fuzzy Discriminant Locality Preserving Subspace for Visual Recognition,
IEICE(E97-D), No. 9, September 2014, pp. 2434-2442.
WWW Link. 1410
BibRef

Yang, J.Y.[Jing-Yu], Gan, Z.Q.[Zi-Qiao], Wu, Z.Y.[Zhao-Yang], Hou, C.P.[Chun-Ping],
Estimation of Signal-Dependent Noise Level Function in Transform Domain via a Sparse Recovery Model,
IP(24), No. 5, May 2015, pp. 1561-1572.
IEEE DOI 1504
BibRef
Earlier: A1, A3, A4, Only:
Estimation of signal-dependent sensor noise via sparse representation of noise level functions,
ICIP12(673-676).
IEEE DOI 1302
discrete cosine transforms BibRef

Ülkü, I.[Irem], Töreyin, B.U.[Behçet Ugur],
Sparse coding of hyperspectral imagery using online learning,
SIViP(9), No. 4, May 2015, pp. 959-966.
Springer DOI 1504
BibRef

Gao, Q.X.[Quan-Xue], Huang, Y.F.[Yun-Fang], Zhang, H.L.[Hai-Lin], Hong, X.[Xin], Li, K.[Kui], Wang, Y.[Yong],
Discriminative sparsity preserving projections for image recognition,
PR(48), No. 8, 2015, pp. 2543-2553.
Elsevier DOI 1505
Dimensionality reduction BibRef

Xu, Y.[Yong], Sun, Y.P.[Yu-Ping], Quan, Y.[Yuhui], Zheng, B.[Bo],
Discriminative structured dictionary learning with hierarchical group sparsity,
CVIU(136), No. 1, 2015, pp. 59-68.
Elsevier DOI 1506
Discriminative dictionary learning BibRef

Quan, Y.H.[Yu-Hui], Xu, Y.[Yong], Sun, Y.P.[Yu-Ping], Huang, Y.[Yan],
Supervised dictionary learning with multiple classifier integration,
PR(55), No. 1, 2016, pp. 247-260.
Elsevier DOI 1604
Sparse coding BibRef

Hettiarachchi, R., Peters, J.F.,
Multi-manifold LLE learning in pattern recognition,
PR(48), No. 9, 2015, pp. 2947-2960.
Elsevier DOI 1506
Locally linear embedding. Multi-manifolds BibRef

Ni, B.B.[Bing-Bing], Moulin, P.[Pierre], Yan, S.C.[Shui-Cheng],
Order Preserving Sparse Coding,
PAMI(37), No. 8, August 2015, pp. 1615-1628.
IEEE DOI 1507
BibRef
Earlier:
Order-Preserving Sparse Coding for Sequence Classification,
ECCV12(II: 173-187).
Springer DOI 1210
Dictionaries BibRef

Zhang, L.[Li], Leng, Y.Q.[Yi-Qin], Yang, J.W.[Ji-Wen], Li, F.Z.[Fan-Zhang],
Supervised locally linear embedding algorithm based on orthogonal matching pursuit,
IET-IPR(9), No. 8, 2015, pp. 626-633.
DOI Link 1506
image classification BibRef

Qian, L.Q.[Li-Qiang], Zhang, L.[Li], Bao, X.[Xing], Li, F.Z.[Fan-Zhang], Yang, J.W.[Ji-Wen],
Supervised sparse neighbourhood preserving embedding,
IET-IPR(11), No. 3, March 2017, pp. 190-199.
DOI Link 1703
BibRef

Wen, B.[Bihan], Ravishankar, S.[Saiprasad], Bresler, Y.[Yoram],
Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications,
IJCV(114), No. 2-3, September 2015, pp. 137-167.
Springer DOI 1509
BibRef
And:
Video denoising by online 3D sparsifying transform learning,
ICIP15(118-122)
IEEE DOI 1512
BibRef
Earlier:
Learning overcomplete sparsifying transforms with block cosparsity,
ICIP14(803-807)
IEEE DOI 1502
Big data. Analytical models BibRef

Wen, B.[Bihan], Ravishankar, S.[Saiprasad], Bresler, Y.[Yoram],
Learning flipping and rotation invariant sparsifying transforms,
ICIP16(3857-3861)
IEEE DOI 1610
Clustering algorithms BibRef

Ravishankar, S.[Saiprasad], Bresler, Y.[Yoram],
Efficient Blind Compressed Sensing Using Sparsifying Transforms with Convergence Guarantees and Application to Magnetic Resonance Imaging,
SIIMS(8), No. 4, 2015, pp. 2519-2557.
DOI Link 1601
BibRef

Jahromi, M.N.S.[Mohammad N. S.], Salman, M.S.[Mohammad Shukri], Hocanin, A.[Aykut], Kukrer, O.[Osman],
Convergence analysis of the zero-attracting variable step-size LMS algorithm for sparse system identification,
SIViP(9), No. 6, September 2015, pp. 1353-1356.
Springer DOI 1509
BibRef

Jahromi, M.N.S.[Mohammad N. S.], Salman, M.S.[Mohammad Shukri], Hocanin, A.[Aykut], Kukrer, O.[Osman],
Mean-square deviation analysis of the zero-attracting variable step-size LMS algorithm,
SIViP(11), No. 3, March 2017, pp. 533-540.
Springer DOI 1702
BibRef

Aliyu, M.L.[Muhammad Lawan], Alkassim, M.A.[Mujahid Ado], Salman, M.S.[Mohammad Shukri],
A p-norm variable step-size LMS algorithm for sparse system identification,
SIViP(9), No. 7, October 2015, pp. 1559-1565.
Springer DOI 1509
BibRef

Xie, J.N.[Jia-Nwen], Hu, W.Z.[Wen-Ze], Zhu, S.C.[Song-Chun], Wu, Y.N.[Ying Nian],
Learning Sparse FRAME Models for Natural Image Patterns,
IJCV(114), No. 2-3, September 2015, pp. 91-112.
Springer DOI 1509
BibRef
Earlier:
Learning Inhomogeneous FRAME Models for Object Patterns,
CVPR14(1035-1042)
IEEE DOI 1409
Energy-based models FRAME (Filters, Random field, And Maximum Entropy). BibRef

Dai, J.F.[Ji-Feng], Hong, Y.[Yi], Hu, W.Z.[Wen-Ze], Zhu, S.C.[Song-Chun], Wu, Y.N.[Ying Nian],
Unsupervised Learning of Dictionaries of Hierarchical Compositional Models,
CVPR14(2505-2512)
IEEE DOI 1409
BibRef

Nazzal, M., Yeganli, F., Ozkaramanli, H.,
A Strategy for Residual Component-Based Multiple Structured Dictionary Learning,
SPLetters(22), No. 11, November 2015, pp. 2059-2063.
IEEE DOI 1509
signal representation BibRef

Chen, J., Chau, L.,
Multiscale Dictionary Learning via Cross-Scale Cooperative Learning and Atom Clustering for Visual Signal Processing,
CirSysVideo(25), No. 9, September 2015, pp. 1457-1468.
IEEE DOI 1509
Clustering algorithms. multi-scale sparse representation. BibRef

Thom, M.[Markus], Rapp, M.[Matthias], Palm, G.[Günther],
Efficient Dictionary Learning with Sparseness-Enforcing Projections,
IJCV(114), No. 2-3, September 2015, pp. 168-194.
Springer DOI 1509
BibRef

Chabiron, O.[Olivier], Malgouyres, F.[François], Tourneret, J.Y.[Jean-Yves], Dobigeon, N.[Nicolas],
Toward Fast Transform Learning,
IJCV(114), No. 2-3, September 2015, pp. 195-216.
Springer DOI 1509
BibRef

Fawzi, A.[Alhussein], Davies, M.[Mike], Frossard, P.[Pascal],
Dictionary Learning for Fast Classification Based on Soft-thresholding,
IJCV(114), No. 2-3, September 2015, pp. 306-321.
Springer DOI 1509
BibRef

Ji, J.Q.[Jian-Qiu], Li, J.M.[Jian-Min], Tian, Q.[Qi], Yan, S.C.[Shui-Cheng], Zhang, B.[Bo],
Angular-Similarity-Preserving Binary Signatures for Linear Subspaces,
IP(24), No. 11, November 2015, pp. 4372-4380.
IEEE DOI 1509
computer vision BibRef

Fukui, K., Maki, A.,
Difference Subspace and Its Generalization for Subspace-Based Methods,
PAMI(37), No. 11, November 2015, pp. 2164-2177.
IEEE DOI 1511
feature extraction BibRef

Camerlenghi, F.[Federico], Villa, E.[Elena],
Optimal Bandwidth of the Minkowski Content-Based Estimator of the Mean Density of Random Closed Sets: Theoretical Results and Numerical Experiments,
JMIV(53), No. 3, November 2015, pp. 264-287.
Springer DOI 1511
BibRef

Tao, J.[Jian_Wen], Wen, S.T.[Shi-Ting], Hu, W.J.[Wen-Jun],
Robust domain adaptation image classification via sparse and low rank representation,
JVCIR(33), No. 1, 2015, pp. 134-148.
Elsevier DOI 1512
Robust domain adaptation learning BibRef

Tao, J.W.[Jian-Wen], Song, D.[Dawei], Wen, S.T.[Shi-Ting], Hu, W.J.[Wen-Jun],
Robust multi-source adaptation visual classification using supervised low-rank representation,
PR(61), No. 1, 2017, pp. 47-65.
Elsevier DOI 1705
Multiple source domain adaptation BibRef

Li, X.[Xiao], Fang, M.[Min], Zhang, J.J.[Ju-Jie],
Projected Transfer Sparse Coding for cross domain image representation,
JVCIR(33), No. 1, 2015, pp. 265-272.
Elsevier DOI 1512
Image representation BibRef

Xu, Y.[Yong], Zhang, B.[Bob], Zhong, Z.F.[Zuo-Feng],
Multiple representations and sparse representation for image classification,
PRL(68, Part 1), No. 1, 2015, pp. 9-14.
Elsevier DOI 1512
Image classification BibRef

Wohlberg, B.[Brendt],
Efficient Algorithms for Convolutional Sparse Representations,
IP(25), No. 1, January 2016, pp. 301-315.
IEEE DOI 1601
BibRef
And:
Convolutional sparse representations as an image model for impulse noise restoration,
IVMSP16(1-5)
IEEE DOI 1608
BibRef
And:
Convolutional sparse representation of color images,
Southwest16(57-60)
IEEE DOI 1605
BibRef
Earlier:
Endogenous convolutional sparse representations for transolation invariant image subspace models,
ICIP14(2859-2863)
IEEE DOI 1502
Computational efficiency. Computational modeling. Accuracy BibRef

Wohlberg, B.[Brendt],
Boundary handling for convolutional sparse representations,
ICIP16(1833-1837)
IEEE DOI 1610
Boundary conditions BibRef

Luo, X., Wohlberg, B.[Brendt],
Convolutional Laplacian sparse coding,
Southwest16(133-136)
IEEE DOI 1605
Convolution BibRef

Kelly, P.A., Kibria, S.,
Complex Exponential Pseudomodes of LTI Operators Over Finite Intervals,
SPLetters(23), No. 1, January 2016, pp. 135-138.
IEEE DOI 1601
linear, time-invariant. Radar, ultrasound. Approximation methods BibRef

Xu, M.[Mai], Wang, Z.[Zulin],
A novel double-layer sparse representation approach for unsupervised dictionary learning,
CVIU(143), No. 1, 2016, pp. 1-10.
Elsevier DOI 1601
BibRef
Earlier:
Unsupervised dictionary learning with double-layer sparse representation,
WACV14(548-555)
IEEE DOI 1406
Sparse representation Dictionaries BibRef

Zheng, H.X.[Hai-Xia], Ip, H.H.S.[Horace H.S.],
Image classification and annotation based on robust regularized coding,
SIViP(10), No. 1, January 2016, pp. 55-64.
Springer DOI 1601
Sparse coding. Geometric and local. BibRef

Li, P.[Ping], Bu, J.J.[Jia-Jun], Yu, J.[Jun], Chen, C.[Chun],
Towards robust subspace recovery via sparsity-constrained latent low-rank representation,
JVCIR(37), No. 1, 2016, pp. 46-52.
Elsevier DOI 1603
Latent low-rank representation BibRef

Karygianni, S.[Sofia], Frossard, P.[Pascal],
Sparse molecular image representation,
JVCIR(36), No. 1, 2016, pp. 213-228.
Elsevier DOI 1603
BibRef
And:
Learning from sparse codes,
ICIP16(3862-3866)
IEEE DOI 1610
Algorithm design and analysis BibRef

Bao, C.L.[Cheng-Long], Ji, H.[Hui], Quan, Y.H.[Yu-Hui], Shen, Z.W.[Zuo-Wei],
Dictionary Learning for Sparse Coding: Algorithms and Convergence Analysis,
PAMI(38), No. 7, July 2016, pp. 1356-1369.
IEEE DOI 1606
BibRef
Earlier:
L0 Norm Based Dictionary Learning by Proximal Methods with Global Convergence,
CVPR14(3858-3865)
IEEE DOI 1409
BibRef
Earlier: A1, A3, A2, Only:
A Convergent Incoherent Dictionary Learning Algorithm for Sparse Coding,
ECCV14(VI: 302-316).
Springer DOI 1408
dictionary learning; global convergence; proximal method BibRef

Yang, L.[Liu], Jing, L.P.[Li-Ping], Ng, M.K.[Michael K.], Yu, J.[Jian],
A discriminative and sparse topic model for image classification and annotation,
IVC(51), No. 1, 2016, pp. 22-35.
Elsevier DOI 1606
Graphical model BibRef

Shen, X.Y.[Xin-Yue], Chen, L.[Laming], Gu, Y.T.[Yuan-Tao], So, H.C.,
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Convex Envelopes for Low Rank Approximation,
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Springer DOI 1504
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CVPR16(5887-5895)
IEEE DOI 1612
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Larsson, V.[Viktor], Olsson, C.[Carl], Bylow, E.[Erik], Kahl, F.[Fredrik],
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Su, T.F.[Te-Feng], Chiang, C.K.[Chen-Kuo], Lai, S.H.[Shang-Hong],
A Multiattribute Sparse Coding Approach for Action Recognition From a Single Unknown Viewpoint,
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gesture recognition BibRef

Chiang, C.K.[Chen-Kuo], Su, T.F.[Te-Feng], Yen, C.[Chih], Lai, S.H.[Shang-Hong],
Multi-attributed Dictionary Learning for Sparse Coding,
ICCV13(1137-1144)
IEEE DOI 1403
Dictionary learning; multiple attributes; sparse coding BibRef

Kim, E.[Eunwoo], Lee, M.[Minsik], Oh, S.[Songhwai],
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data structures BibRef

Gao, S.H.[Sheng-Hua], Zeng, Z.N.[Zi-Nan], Jia, K.[Kui], Chan, T.H.[Tsung-Han], Tang, J.H.[Jin-Hui],
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IEEE DOI 1609
Accuracy. sparse representation. BibRef

Ji, H.K.[Hong-Kun], Sun, Q.S.[Quan-Sen], Yuan, Y.H.[Yun-Hao], Ji, Z.X.[Ze-Xuan],
C2DMCP: View-consistent collaborative discriminative multiset correlation projection for data representation,
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Elsevier DOI 1610
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Bian, X.[Xiao], Krim, H.[Hamid], Bronstein, A.[Alex], Dai, L.[Liyi],
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Adaptive maximum margin analysis for image recognition,
PR(61), No. 1, 2017, pp. 339-347.
Elsevier DOI 1609
Maximum margin BibRef

Zhan, Y.Z.[Yong-Zhao], Liu, J.[Junqi], Gou, J.P.[Jian-Ping], Wang, M.C.[Min-Chao],
A video semantic detection method based on locality-sensitive discriminant sparse representation and weighted KNN,
JVCIR(41), No. 1, 2016, pp. 65-73.
Elsevier DOI 1612
Locality-sensitive discriminant sparse representation method (LSDSR). BibRef

Zhang, S.Z.[Shi-Zhou], Wang, J.[Jinjun], Tao, X.[Xiaoyu], Gong, Y.H.[Yi-Hong], Zheng, N.N.[Nan-Ning],
Constructing Deep Sparse Coding Network for image classification,
PR(64), No. 1, 2017, pp. 130-140.
Elsevier DOI 1701
Sparse Coding BibRef

Luu, K.[Khoa], Savvides, M.[Marios], Bui, T.D.[Tien D.], Suen, C.Y.[Ching Y.],
Compressed Submanifold Multifactor Analysis,
PAMI(39), No. 3, March 2017, pp. 444-456.
IEEE DOI 1702
BibRef
Earlier:
Compressed Submanifold Multifactor Analysis with adaptive factor structures,
ICPR12(2715-2718).
WWW Link. 1302
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Hsaio, W.H.[Wen-Hoar], Liu, C.L.[Chien-Liang], Wu, W.L.[Wei-Liang],
Locality-constrained max-margin sparse coding,
PR(65), No. 1, 2017, pp. 285-295.
Elsevier DOI 1702
Locality BibRef

Lim, K.L., Wang, H.,
Sparse Coding Based Fisher Vector Using a Bayesian Approach,
SPLetters(24), No. 1, January 2017, pp. 91-95.
IEEE DOI 1702
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And: Corrections: SPLetters(24), No. 4, April 2017, pp. 520-520.
IEEE DOI 1704
Encoding; Signal processing algorithms; Sparse matrices. Gaussian distribution BibRef

Sankaran, A.[Anush], Vatsa, M.[Mayank], Singh, R.[Richa], Majumdar, A.[Angshul],
Group sparse autoencoder,
IVC(60), No. 1, 2017, pp. 64-74.
Elsevier DOI 1704
Supervised autoencoder BibRef

Yadav, S., Singh, M., Vatsa, M.[Mayank], Singh, R.[Richa], Majumdar, A.[Angshul],
Low rank group sparse representation based classifier for pose variation,
ICIP16(2986-2990)
IEEE DOI 1610
Classification algorithms BibRef

Liu, S.G.[Shi-Gang], Li, L.J.[Ling-Jun], Peng, Y.[Yali], Qiu, G.Y.[Guo-Yong], Lei, T.[Tao],
Improved sparse representation method for image classification,
IET-CV(11), No. 4, June 2017, pp. 319-330.
DOI Link 1705
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Liao, Y.Y.[Yi-Yi], Wang, Y.[Yue], Liu, Y.[Yong],
Graph Regularized Auto-Encoders for Image Representation,
IP(26), No. 6, June 2017, pp. 2839-2852.
IEEE DOI 1705
Jacobian matrices, computer vision, graph theory, image classification, image coding, image representation, learning (artificial intelligence), pattern clustering, GAE, Jacobian matrix, clustering, complex modeling, computer vision, deep architectures, deep representation learning techniques, encoder mapping, encoding model, graph regularized autoencoders, hidden representation space, high-dimensional input space, image classification, image clustering, image representation, intrinsic low-dimensional manifold, local invariant deep nonlinear mapping algorithm, manifold learning, weight matrix, weighted Frobenius norm, Algorithm design and analysis, Decoding, Image reconstruction, Image representation, Inference algorithms, Jacobian matrices, Manifolds, Auto-encoders, graph regularization, local, invariance BibRef

Eftekhari, A., Balzano, L., Wakin, M.B.,
What to Expect When You Are Expecting on the Grassmannian,
SPLetters(24), No. 6, June 2017, pp. 872-876.
IEEE DOI 1705
Coherence, Estimation, Partitioning algorithms, Q measurement, Signal processing algorithms, Size measurement, Standards, Fréchet expectation, Grassmannian averaging, matrix completion, principal component analysis, streaming algorithms, subspace identification BibRef

Zhang, Y.[Yupei], Xiang, M.[Ming], Yang, B.[Bo],
Low-rank preserving embedding,
PR(70), No. 1, 2017, pp. 112-125.
Elsevier DOI 1706
Low-rank, representation BibRef

Shu, Z.Q.[Zhen-Qiu], Fan, H.F.[Hong-Fei], Huang, P.[Pu], Wu, D.[Dong], Ye, F.Y.[Fei-Yue], Wu, X.J.[Xiao-Jun],
Multiple Laplacian graph regularised low-rank representation with application to image representation,
IET-IPR(11), No. 6, June 2017, pp. 370-378.
DOI Link 1706
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Qiao, X.[Xu], Liu, X.Q.[Xiao-Qing], Chen, Y.W.[Yen-Wei], Liu, Z.P.[Zhi-Ping],
Multi-dimensional data representation using linear tensor coding,
IET-IPR(11), No. 7, July 2017, pp. 492-501.
DOI Link 1707
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Prasad, S., Labate, D., Cui, M., Zhang, Y.,
Morphologically Decoupled Structured Sparsity for Rotation-Invariant Hyperspectral Image Analysis,
GeoRS(55), No. 8, August 2017, pp. 4355-4366.
IEEE DOI 1708
Dictionaries, Feature extraction, Hyperspectral imaging, Image analysis, Robustness, Training, Hyperspectral data, image analysis, multiresolution analysis, sparse representation BibRef

Wang, W.[Wen], Wang, R.P.[Rui-Ping], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Prototype Discriminative Learning for Image Set Classification,
SPLetters(24), No. 9, September 2017, pp. 1318-1322.
IEEE DOI 1708
BibRef
Earlier:
Prototype Discriminative Learning for Face Image Set Classification,
ACCV16(III: 344-360).
Springer DOI 1704
Databases, Optimization, Prototypes, Robustness, Signal processing algorithms, Testing, Training, Discriminative learning, image set classification, prototype, learning BibRef

Wang, R.P.[Rui-Ping], Guo, H.M.[Hui-Min], Davis, L.S.[Larry S.], Dai, Q.H.[Qiong-Hai],
Covariance discriminative learning: A natural and efficient approach to image set classification,
CVPR12(2496-2503).
IEEE DOI 1208
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Zhang, Y.M.[Yang-Muzi], Jiang, Z.L.[Zhuo-Lin], Davis, L.S.[Larry S.],
Discriminative Tensor Sparse Coding for Image Classification,
BMVC13(xx-yy).
DOI Link 1402
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And:
Learning Structured Low-Rank Representations for Image Classification,
CVPR13(676-683)
IEEE DOI 1309
dictionary learning; image classification; low-rank representation BibRef

Zhang, G.X.[Guang-Xiao], Jiang, Z.L.[Zhuo-Lin], Davis, L.S.[Larry S.],
Online Semi-Supervised Discriminative Dictionary Learning for Sparse Representation,
ACCV12(I:259-273).
Springer DOI 1304
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Zheng, J.J.[Jing-Jing], Jiang, Z.L.[Zhuo-Lin],
Tag Taxonomy Aware Dictionary Learning for Region Tagging,
CVPR13(369-376)
IEEE DOI 1309
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Yao, C.[Chao], Liu, Y.F.[Ya-Feng], Jiang, B.[Bo], Han, J.G.[Jun-Gong], Han, J.W.[Jun-Wei],
LLE Score: A New Filter-Based Unsupervised Feature Selection Method Based on Nonlinear Manifold Embedding and Its Application to Image Recognition,
IP(26), No. 11, November 2017, pp. 5257-5269.
IEEE DOI 1709
feature selection, handwriting recognition, face image classification, handwriting digits data set, Correlation, BibRef

Ji, R., Liu, H., Cao, L., Liu, D., Wu, Y., Huang, F.,
Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding,
IP(26), No. 11, November 2017, pp. 5411-5420.
IEEE DOI 1709
Acceleration, Binary codes, Image reconstruction, Manifolds, Matrix decomposition, Optimization, Discrete locally linear embedding, hashing, manifold learning, visual search BibRef

Li, J., Wu, Y., Zhao, J., Lu, K.,
Low-Rank Discriminant Embedding for Multiview Learning,
Cyber(47), No. 11, November 2017, pp. 3516-3529.
IEEE DOI 1710
Euclidean distance, Face, Kernel, Laplace equations, Manifolds, Robustness, Training, Graph embedding, low-rank representation (LRR), multiview learning, subspace, learning BibRef

Gu, J.[Jing], Jiao, L.C.[Li-Cheng], Liu, F.[Fang], Yang, S.Y.[Shu-Yuan], Wang, R.F.[Rong-Fang], Chen, P.[Puhua], Cui, Y.H.[Yuan-Hao], Xie, J.H.[Jun-Hu], Zhang, Y.[Yake],
Random subspace based ensemble sparse representation,
PR(74), No. 1, 2018, pp. 544-555.
Elsevier DOI 1711
Random subspace BibRef


Dutta, A., Li, X.,
A fast algorithm for a weighted low rank approximation,
MVA17(93-96)
DOI Link 1708
Algorithm design and analysis, Analytical models, Approximation algorithms, Estimation, Matrix decomposition, Principal component analysis, Robustness BibRef

Zhang, L.F.[Li-Fang], Shen, Q.[Qi], Li, D.F.[De-Fang], Tang, X.[Xin], Wang, P.S.[Patrick S.], Feng, G.C.[Guo-Can],
Adaptive Hashing with Sparse Modification,
ICPR16(3844-3849)
IEEE DOI 1705
Binary codes, Distortion, Hypercubes, Linear programming, Principal component analysis, Quantization (signal), Sparse, matrices BibRef

de Souza, L.S.[Lincon Sales], Hino, H.[Hideitsu], Fukui, K.[Kazuhiro],
3D Object Recognition with Enhanced Grassmann Discriminant Analysis,
HIS16(III: 345-359).
Springer DOI 1704
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Wang, S.R.[Shu-Run], Zhao, Z.H.[Zheng-Hui], Zhang, X.[Xiang], Zhang, J.[Jian], Wang, S.Q.[Shi-Qi], Ma, S.W.[Si-Wei], Gao, W.[Wen],
Improved entropy of primitive for visual information estimation,
VCIP16(1-4)
IEEE DOI 1701
Convergence BibRef

Qi, N.[Na], Shi, Y.H.[Yun-Hui], Sun, X.Y.[Xiao-Yan], Yin, B.C.[Bao-Cai],
TenSR: Multi-dimensional Tensor Sparse Representation,
CVPR16(5916-5925)
IEEE DOI 1612
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Bernard, F.[Florian], Gemmar, P.[Peter], Hertel, F.[Frank], Goncalves, J.[Jorge], Thunberg, J.[Johan],
Linear Shape Deformation Models with Local Support Using Graph-Based Structured Matrix Factorisation,
CVPR16(5629-5638)
IEEE DOI 1612
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Wei, X.[Xian], Shen, H.[Hao], Kleinsteuber, M.[Martin],
Trace Quotient Meets Sparsity: A Method for Learning Low Dimensional Image Representations,
CVPR16(5268-5277)
IEEE DOI 1612
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Chakraborty, R.[Rudrasis], Seo, D.H.[Do-Hyung], Vemuri, B.C.[Baba C.],
An Efficient Exact-PGA Algorithm for Constant Curvature Manifolds,
CVPR16(3976-3984)
IEEE DOI 1612
A non-linear analog of the PCA algorithm, Principal Geodesic Analysis (PGA). BibRef

Chen, B.[Boheng], Li, J.[Jie], Ma, B.[Biyun], Wei, G.[Gang],
Convolutional sparse coding classification model for image classification,
ICIP16(1918-1922)
IEEE DOI 1610
Convolution BibRef

Hsieh, S.H.[Sung-Hsien], Lu, C.S.[Chun-Shien], Pei, S.C.[Soo-Chang],
Fast binary embedding via circulant downsampled matrix,
ICIP16(1789-1793)
IEEE DOI 1610
Algorithm design and analysis BibRef

Siyahjani, F.[Farzad], Almohsen, R.[Ranya], Sabri, S.[Sinan], Doretto, G.[Gianfranco],
A Supervised Low-Rank Method for Learning Invariant Subspaces,
ICCV15(4220-4228)
IEEE DOI 1602
Matrix decomposition BibRef

Siyahjani, F.[Farzad], Doretto, G.[Gianfranco],
Learning a Context Aware Dictionary for Sparse Representation,
ACCV12(II:228-241).
Springer DOI 1304
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Chum, O.[Ondrej],
Low Dimensional Explicit Feature Maps,
ICCV15(4077-4085)
IEEE DOI 1602
Computer vision BibRef

Sharma, G., Schiele, B.,
Scalable Nonlinear Embeddings for Semantic Category-Based Image Retrieval,
ICCV15(1296-1304)
IEEE DOI 1602
Approximation algorithms BibRef

Wang, X.F.[Xiao-Fei], Navasca, C.[Carmeliza],
Adaptive Low Rank Approximation for Tensors,
RSL-CV15(939-945)
IEEE DOI 1602
Adaptation models BibRef

Majumdar, A.[Angshul],
Discriminative label consistent dictionary learning,
ICIP15(1016-1020)
IEEE DOI 1512
Classification BibRef

Bian, X.[Xiao], Krim, H.[Hamid],
Bi-sparsity pursuit for robust subspace recovery,
ICIP15(3535-3539)
IEEE DOI 1512
Sparse representation BibRef

Liu, Q.F.[Qing-Feng], Puthenputhussery, A.[Ajit], Liu, C.J.[Cheng-Jun],
Learning the discriminative dictionary for sparse representation by a general fisher regularized model,
ICIP15(4347-4351)
IEEE DOI 1512
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Provenzi, E.[Edoardo], Delon, J.[Julie], Gousseau, Y.[Yann], Mazin, B.[Baptiste],
On Spatiochromatic Features in Natural Images Statistics,
CIAP15(II:46-55).
Springer DOI 1511
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Xiao, S.J.[Shi-Jie], Li, W.[Wen], Xu, D.[Dong], Tao, D.C.[Da-Cheng],
FaLRR: A fast low rank representation solver,
CVPR15(4612-4620)
IEEE DOI 1510
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Heide, F.[Felix], Heidrich, W.[Wolfgang], Wetzstein, G.[Gordon],
Fast and flexible convolutional sparse coding,
CVPR15(5135-5143)
IEEE DOI 1510
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Zhang, X.[Xin], Phung, D.Q.[Dinh Q.], Venkatesh, S.[Svetha], Pham, D.S.[Duc-Son], Liu, W.Q.[Wan-Quan],
Multi-View Subspace Clustering for Face Images,
DICTA15(1-7)
IEEE DOI 1603
computer vision BibRef

Zhang, X.[Xin], Pham, D.S.[Duc-Son], Phung, D.Q.[Dinh Q.], Liu, W.Q.[Wan-Quan], Saha, B.[Budhaditya], Venkatesh, S.[Svetha],
Visual Object Clustering via Mixed-Norm Regularization,
WACV15(1030-1037)
IEEE DOI 1503
Clustering algorithms BibRef

Mukherjee, L.[Lopamudra], Hall, A.[Alex],
Non-negative Sparse Coding with Regularizer for Image Classification,
WACV15(852-859)
IEEE DOI 1503
Dictionaries BibRef

Zhang, H.[Heng], Patel, V.M.[Vishal M.], Shekhar, S.[Sumit], Chellappa, R.[Rama],
Domain adaptive sparse representation-based classification,
FG15(1-8)
IEEE DOI 1508
biometrics (access control) BibRef

Shekhar, S.[Sumit], Patel, V.M.[Vishal M.], Chellappa, R.[Rama],
Analysis sparse coding models for image-based classification,
ICIP14(5207-5211)
IEEE DOI 1502
Algorithm design and analysis BibRef

Lu, K.[Keyu], Li, J.[Jian], An, X.J.[Xiang-Jing], He, H.[Hangen],
Hierarchical image representation via multi-level sparse coding,
ICIP14(4902-4906)
IEEE DOI 1502
Dictionaries BibRef

Silva, R.F.[Rogers F.], Plis, S.M.[Sergey M.], Adali, T.[Tulay], Calhoun, V.D.[Vince D.],
Multidataset independent subspace analysis extends independent vector analysis,
ICIP14(2864-2868)
IEEE DOI 1502
Cost function BibRef

Liu, G.[Gaowen], Yan, Y.[Yan], Song, J.[Jingkuan], Sebe, N.[Nicu],
Minimizing dataset bias: Discriminative multi-task sparse coding through shared subspace learning for image classification,
ICIP14(2869-2873)
IEEE DOI 1502
Accuracy BibRef

Lin, T.Y.[Tsung-Yu], Liu, T.L.[Tyng-Luh],
Efficient binary codes for extremely high-dimensional data,
ICIP14(2212-2216)
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Qi, Y.G.[Yong-Gang], Zheng, W.S.[Wei-Shi], Xiang, T.[Tao], Song, Y.Z.[Yi-Zhe], Zhang, H.G.[Hong-Gang], Guo, J.[Jun],
One-Shot Learning of Sketch Categories with Co-regularized Sparse Coding,
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Springer DOI 1501
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Wang, Y.[Yuqi], Gong, Y.F.[Yun-Fei], Liu, Q.A.[Qi-Ang],
Robust Attribute-Based Visual Recognition Using Discriminative Latent Representation,
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Discriminative Latent Attribute (DLA) BibRef

Xiang, W.[Wu], Wang, J.M.[Jian-Min], Long, M.S.[Ming-Sheng],
Local Hybrid Coding for Image Classification,
ICPR14(3744-3749)
IEEE DOI 1412
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Xing, S.[Sun], Yung, N.H.C.[Nelson H.C.],
Large Scale Image Categorization in Sparse Nonparametric Bayesian Representation,
ICPR14(1365-1370)
IEEE DOI 1412
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Luo, L.[Lei], Yang, J.[Jian], Qian, J.J.[Jian-Jun], Yang, J.Y.[Jing-Yu],
Nuclear Norm Regularized Sparse Coding,
ICPR14(1834-1839)
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Databases BibRef

Li, W.[Wanyi], Wang, P.[Peng], Qiao, H.[Hong],
Visual Tracking via Saliency Weighted Sparse Coding Appearance Model,
ICPR14(4092-4097)
IEEE DOI 1412
Clutter BibRef

Wang, X.Y.[Xiao-Yang], Ji, Q.A.[Qi-Ang],
Attribute Augmentation with Sparse Coding,
ICPR14(4352-4357)
IEEE DOI 1412
Dictionaries BibRef

Choi, J.H.[Jong-Hyun], Cho, H.J.[Hyun-Jong], Kwac, J.[Jungsuk], Davis, L.S.[Larry S.],
Toward Sparse Coding on Cosine Distance,
ICPR14(4423-4428)
IEEE DOI 1412
Accuracy BibRef

Tao, L.[Liang], Ip, H.H.S.[Horace H.S.], Wang, Y.L.[Ying-Lin], Shu, X.[Xin],
Ensemble Manifold Structured Low Rank Approximation for Data Representation,
ICPR14(744-749)
IEEE DOI 1412
Approximation methods BibRef

Li, J.X.[Jun-Xia], Rajan, D.[Deepu], Yang, J.[Jian],
Local feature embedding for supervised image classification,
ICIP15(1300-1304)
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Johnson, J.[Jubin], Varnousfaderani, E.S., Cholakkal, H.[Hisham], Rajan, D.[Deepu],
Sparse Coding for Alpha Matting,
IP(25), No. 7, July 2016, pp. 3032-3043.
IEEE DOI 1606
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And: A1, A4, A3, Only:
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VCIP15(1-4)
IEEE DOI 1605
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BMVC14(xx-yy).
HTML Version. 1410
graph theory. Adaptive optics BibRef

Johnson, J.[Jubin], Cholakkal, H.[Hisham], Rajan, D.[Deepu],
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estimation theory BibRef

Zhao, Z.C.[Zhi-Chen], Ma, H.M.[Hui-Min], Chen, X.Z.[Xiao-Zhi],
Protected Pooling Method of Sparse Coding in Visual Classification,
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Chen, C.[Chen], Huang, J.Z.[Jun-Zhou], He, L.[Lei], Li, H.S.[Hong-Sheng],
Preconditioning for Accelerated Iteratively Reweighted Least Squares in Structured Sparsity Reconstruction,
CVPR14(2713-2720)
IEEE DOI 1409
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Mobahi, H.[Hossein], Liu, C.[Ce], Freeman, W.T.[William T.],
A Compositional Model for Low-Dimensional Image Set Representation,
CVPR14(1322-1329)
IEEE DOI 1409
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Izadinia, H.[Hamid], Sadeghi, F.[Fereshteh], Farhadi, A.[Ali],
Incorporating Scene Context and Object Layout into Appearance Modeling,
CVPR14(232-239)
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Chen, Y.[Yuansi], Mairal, J.[Julien], Harchaoui, Z.[Zaid],
Fast and Robust Archetypal Analysis for Representation Learning,
CVPR14(1478-1485)
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archetypal analysis; sparse coding BibRef

Yang, M.[Meng], Dai, D.X.[Deng-Xin], Shen, L.[Lilin], Van Gool, L.J.[Luc J.],
Latent Dictionary Learning for Sparse Representation Based Classification,
CVPR14(4138-4145)
IEEE DOI 1409
classification;latent dictionary learning;sparse represntation BibRef

Niu, L.[Li], Cai, J.F.[Jian-Fei], Xu, D.[Dong],
Domain Adaptive Fisher Vector for Visual Recognition,
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Niu, L.[Li], Li, W.[Wen], Xu, D.[Dong],
Multi-view Domain Generalization for Visual Recognition,
ICCV15(4193-4201)
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Linear matrix inequalities BibRef

Xu, Z.[Zheng], Li, W.[Wen], Niu, L.[Li], Xu, D.[Dong],
Exploiting Low-Rank Structure from Latent Domains for Domain Generalization,
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Liu, B.D.[Bao-Di], Wang, Y.X.[Yu-Xiong], Shen, B.[Bin], Zhang, Y.J.[Yu-Jin], Hebert, M.[Martial],
Self-explanatory Sparse Representation for Image Classification,
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Landecker, W.[Will], Chartrand, R.[Rick], De Deo, S.[Simon],
Robust Sparse Coding and Compressed Sensing with the Difference Map,
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Talwalkar, A.[Ameet], Mackey, L.[Lester], Mu, Y.D.[Ya-Dong], Chang, S.F.[Shih-Fu], Jordan, M.I.[Michael I.],
Distributed Low-Rank Subspace Segmentation,
ICCV13(3543-3550)
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Distributed BibRef

Huot, E.[Etienne], Papari, G.[Giuseppe], Herlin, I.[Isabelle],
Optimal Orthogonal Basis and Image Assimilation: Motion Modeling,
ICCV13(3352-3359)
IEEE DOI 1403
data assimilation BibRef

Wang, Z.W.[Zhao-Wen], Yang, J.C.[Jian-Chao], Nasrabadi, N.[Nasser], Huang, T.S.[Thomas S.],
A Max-Margin Perspective on Sparse Representation-Based Classification,
ICCV13(1217-1224)
IEEE DOI 1403
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Wu, S.S.[Song-Song], Jing, X.Y.[Xiao-Yuan], Yang, J.[Jian], Yang, J.Y.[Jing-Yu],
Learning image manifold using neighboring similarity integration,
ICIP14(1897-1901)
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Data visualization BibRef

Liu, Q.[Qian], Jing, X.Y.[Xiao-Yuan], Hu, R.M.[Rui-Min], Yao, Y.F.[Yong-Fang], Yang, J.Y.[Jing-Yu],
Similarity preserving analysis based on sparse representation for image feature extraction and classification,
ICIP13(3013-3016)
IEEE DOI 1402
Similarity preserving analysis BibRef

Zhang, H.[Hong], Chen, L.[Li],
Isomorphic and sparse multimodal data representation based on correlation analysis,
ICIP13(3959-3962)
IEEE DOI 1402
correlation analysis BibRef

Bevilacqua, M.[Marco], Roumy, A.[Aline], Guillemot, C.[Christine], Morel, M.L.A.[Marie-Line Alberi],
K-WEB: Nonnegative dictionary learning for sparse image representations,
ICIP13(146-150)
IEEE DOI 1402
Approximation methods BibRef

Han, S.[Sheng], Fu, R.Q.[Rui-Qing], Wang, S.Z.[Su-Zhen], Wu, X.Y.[Xin-Yu],
Online adaptive dictionary learning and weighted sparse coding for abnormality detection,
ICIP13(151-155)
IEEE DOI 1402
Accuracy BibRef

Qi, N.[Na], Shi, Y.H.[Yun-Hui], Sun, X.Y.[Xiao-Yan], Wang, J.D.[Jing-Dong], Ding, W.[Wenpeng],
Two dimensional analysis sparse model,
ICIP13(310-314)
IEEE DOI 1402
Algorithm design and analysis BibRef

Zonoobi, D.[Dornoosh], Kassim, A.A.[Ashraf A.],
Low rank and sparse matrix reconstruction with partial support knowledge for surveillance video processing,
ICIP13(335-339)
IEEE DOI 1402
Algorithm design and analysis BibRef

Shen, L.[Li], Wang, S.H.[Shu-Hui], Sun, G.[Gang], Jiang, S.Q.[Shu-Qiang], Huang, Q.M.[Qing-Ming],
Multi-level Discriminative Dictionary Learning towards Hierarchical Visual Categorization,
CVPR13(383-390)
IEEE DOI 1309
Categorization; Dictionary learning; Hierarchical structure BibRef

Bo, L.F.[Lie-Feng], Ren, X.F.[Xiao-Feng], Fox, D.[Dieter],
Multipath Sparse Coding Using Hierarchical Matching Pursuit,
CVPR13(660-667)
IEEE DOI 1309
Deep Learning; Feature Learning; Object Recognition; Sparse Coding BibRef

Bristow, H.[Hilton], Eriksson, A.P.[Anders P.], Lucey, S.[Simon],
Fast Convolutional Sparse Coding,
CVPR13(391-398)
IEEE DOI 1309
ADMM; convolution; deep learning; fourier; sparse coding BibRef

Chi, Y.T.[Yu-Tseh], Ali, M.[Mohsen], Rushdi, M.[Muhammad], Ho, J.[Jeffrey],
Affine-Constrained Group Sparse Coding and Its Application to Image-Based Classifications,
ICCV13(681-688)
IEEE DOI 1403
Sparse coding; affine; classification; group BibRef

Chi, Y.T.[Yu-Tseh], Ali, M.[Mohsen], Rajwade, A.[Ajit], Ho, J.[Jeffrey],
Block and Group Regularized Sparse Modeling for Dictionary Learning,
CVPR13(377-382)
IEEE DOI 1309
block group; dictionary learning; sparse coding BibRef

Khan, N.[Nazar], Tappen, M.F.[Marshall F.],
Discriminative dictionary learning with spatial priors,
ICIP13(166-170)
IEEE DOI 1402
BibRef
Earlier:
Stable discriminative dictionary learning via discriminative deviation,
ICPR12(3224-3227).
WWW Link. 1302
Dictionaries BibRef

Pang, J.B.[Jun-Biao], Huang, Q.M.[Qing-Ming], Yin, B.C.[Bao-Cai], Qin, L.[Lei], Wang, D.[Dan],
Stochastic boosting for large-scale image classification,
ICIP13(3274-3277)
IEEE DOI 1402
BibRef
Earlier:
Theoretical analysis of learning local anchors for classification,
ICPR12(1803-1806).
WWW Link. 1302
Boosting. local coordinate coding. BibRef

Wang, Y.M.[Yue-Ming], Wang, X.G.[Xing-Gang], Zhu, S.J.[Shao-Jun], Bai, X.[Xiang], Liu, W.Y.[Wen-Yu],
Adjacent coding for image classification,
ICPR12(1459-1462).
WWW Link. 1302
encode one descriptor and its adjacent neighbors. BibRef

Ou, W.H.[Wei-Hua], You, X.[Xinge], Cheung, Y.M.[Yiu-Ming], Peng, Q.[Qinmu], Gong, M.M.[Ming-Ming], Jiang, X.[Xiubao],
Structured sparse coding for image representation based on L1-graph,
ICPR12(3220-3223).
WWW Link. 1302
BibRef

Han, X.H.[Xian-Hua], Qiao, X.[Xu], Chen, Y.W.[Yen-Wei],
Group sparse representation of adaptive sub-domain selection for image classification,
ICPR12(1431-1434).
WWW Link. 1302
BibRef

Paris, S.[Sebastien], Halkias, X.[Xanadu], Glotin, H.[Herve],
Sparse coding for histograms of local binary patterns applied for image categorization: Toward a Bag-of-Scenes analysis,
ICPR12(2817-2820).
WWW Link. 1302
BibRef

Wang, J.[Jin], Sun, X.P.[Xiang-Ping], Chen, R.H.[Rong-Hua], She, M.[Mary], Wang, Q.A.[Qi-Ang],
Object categorization via sparse representation of local features,
ICPR12(3005-3008).
WWW Link. 1302
BibRef

Duan, G.F.[Gui-Fang], Wang, H.C.[Hong-Cui], Liu, Z.Y.[Zhen-Yu], Deng, J.P.[Jun-Ping], Chen, Y.W.[Yen-Wei],
K-CPD: Learning of overcomplete dictionaries for tensor sparse coding,
ICPR12(493-496).
WWW Link. 1302
BibRef

Lin, T.[Tong], Liu, S.[Shi], Zha, H.B.[Hong-Bin],
Incoherent dictionary learning for sparse representation,
ICPR12(1237-1240).
WWW Link. 1302
BibRef

Guo, S.[Song], Ruan, Q.Q.[Qiu-Qi], Miao, Z.J.[Zhen-Jiang],
Similarity weighted sparse representation for classification,
ICPR12(1241-1244).
WWW Link. 1302
BibRef

Thiagarajan, J.J.[Jayaraman J.], Ramamurthy, K.N.[Karthikeyan Natesan], Sattigeri, P.[Prasanna], Spanias, A.[Andreas],
Supervised local sparse coding of sub-image features for image retrieval,
ICIP12(3117-3120).
IEEE DOI 1302
BibRef

Zhang, L.[Lihe], Ma, C.[Chen],
Low-rank, sparse matrix decomposition and group sparse coding for image classification,
ICIP12(669-672).
IEEE DOI 1302
BibRef

Raja, R., Mansoor Roomi, S.M., Dharmalakshmi, D.,
Robust indoor/outdoor scene classification,
ICAPR15(1-5)
IEEE DOI 1511
BibRef
Earlier:
Outdoor scene classification using invariant features,
NCVPRIPG13(1-4)
IEEE DOI 1408
Gabor filters. feature extraction BibRef

Sathyabama, B., Mansoor Roomi, S.M., Kamalam R, E.J.,
Geometric invariant Target classification using 2D Mellin cepstrum with modified grid formation,
NCVPRIPG13(1-4)
IEEE DOI 1408
Fourier transforms BibRef

Raja, R., Mansoor Roomi, S.M., Kalaiyarasi, D.,
Semantic modeling of natural scenes by local binary pattern,
IMVIP12(169-172).
IEEE DOI 1302
BibRef

Julazadeh, A.[Ali], Marsousi, M.[Mahdi], Alirezaie, J.[Javad],
Classification based on sparse representation and Euclidian distance,
VCIP12(1-5).
IEEE DOI 1302
BibRef

Zeng, Z.[Zinan], Chan, T.H.[Tsung-Han], Jia, K.[Kui], Xu, D.[Dong],
Finding Correspondence from Multiple Images via Sparse and Low-Rank Decomposition,
ECCV12(V: 325-339).
Springer DOI 1210
BibRef

Xia, W.[Wei], Song, Z.[Zheng], Feng, J.S.[Jia-Shi], Cheong, L.F.[Loong-Fah], Yan, S.C.[Shui-Cheng],
Segmentation over Detection by Coupled Global and Local Sparse Representations,
ECCV12(V: 662-675).
Springer DOI 1210
BibRef

Jiang, Z.L.[Zhuo-Lin], Davis, L.S.[Larry S.],
Submodular Salient Region Detection,
CVPR13(2043-2050)
IEEE DOI 1309
BibRef

Guo, H.M.[Hui-Min], Jiang, Z.L.[Zhuo-Lin], Davis, L.S.[Larry S.],
Discriminative Dictionary Learning with Pairwise Constraints,
ACCV12(I:328-342).
Springer DOI 1304
BibRef

Jiang, Z.L.[Zhuo-Lin], Lin, Z.[Zhe], Davis, L.S.[Larry S.],
Learning a discriminative dictionary for sparse coding via label consistent K-SVD,
CVPR11(1697-1704).
IEEE DOI 1106
BibRef

Jiang, Z.L.[Zhuo-Lin], Zhang, G.X.[Guang-Xiao], Davis, L.S.[Larry S.],
Submodular dictionary learning for sparse coding,
CVPR12(3418-3425).
IEEE DOI 1208
BibRef

Yang, F.[Fan], Jiang, Z.L.[Zhuo-Lin], Davis, L.S.[Larry S.],
Online discriminative dictionary learning for visual tracking,
WACV14(854-861)
IEEE DOI 1406
Dictionaries;Equations;Joints;Target tracking;Training;Visualization BibRef

Wang, F.[Fang], Han, H.[Hu], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Deep Multi-Task Learning for Joint Prediction of Heterogeneous Face Attributes,
FG17(173-179)
IEEE DOI 1707
Correlation, Databases, Face, Feature extraction, Hair, Image color analysis, Predictive, models BibRef

Cao, L.J.[Liu-Juan], Ji, R.R.[Rong-Rong], Gao, Y.[Yue], Yang, Y.[Yi], Tian, Q.[Qi],
Weakly supervised sparse coding with geometric consistency pooling,
CVPR12(3578-3585).
IEEE DOI 1208
BibRef

Liu, H.F.[Hai-Feng], Yang, Z.[Zheng], Wu, Z.H.[Zhao-Hui], Li, X.L.[Xue-Long],
A-Optimal Non-negative Projection for image representation,
CVPR12(1592-1599).
IEEE DOI 1208
BibRef

Liu, R.S.[Ri-Sheng], Lin, Z.C.[Zhou-Chen], de la Torre, F.[Fernando], Su, Z.X.[Zhi-Xun],
Fixed-rank representation for unsupervised visual learning,
CVPR12(598-605).
IEEE DOI 1208
BibRef

Liu, L.Q.[Ling-Qiao], Wang, L.[Lei], Liu, X.W.[Xin-Wang],
In defense of soft-assignment coding,
ICCV11(2486-2493).
IEEE DOI 1201
Computationally efficient, but not as accurate as sparse or local coding (which is computationally more expensive) BibRef

Sohn, K.[Kihyuk], Jung, D.Y.[Dae Yon], Lee, H.L.[Hong-Lak], Hero, A.O.[Alfred O.],
Efficient learning of sparse, distributed, convolutional feature representations for object recognition,
ICCV11(2643-2650).
IEEE DOI 1201
BibRef

Robles-Kelly, A.[Antonio],
Learning a Gaussian basis for spectra representation aimed at reflectance classification,
OTCBVS11(88-95).
IEEE DOI 1106
BibRef

Shi, J.P.[Jian-Ping], Ren, X.[Xiang], Dai, G.[Guang], Wang, J.D.[Jing-Dong], Zhang, Z.H.[Zhi-Hua],
A non-convex relaxation approach to sparse dictionary learning,
CVPR11(1809-1816).
IEEE DOI 1106
To learn sparse representation (few words to describe it). Concave approach. BibRef

Zontak, M.[Maria], Irani, M.[Michal],
Internal statistics of a single natural image,
CVPR11(977-984).
IEEE DOI 1106
From recurrence of small image patches. Priors for solving problems. BibRef

Cai, D.[Deng], Bao, H.J.[Hu-Jun], He, X.F.[Xiao-Fei],
Sparse concept coding for visual analysis,
CVPR11(2905-2910).
IEEE DOI 1106
Sparse Concept Coding, to capture geometric structure more than SVD does. BibRef

He, R.[Ran], Zheng, W.S.[Wei-Shi], Hu, B.G.[Bao-Gang], Kong, X.W.[Xiang-Wei],
Nonnegative sparse coding for discriminative semi-supervised learning,
CVPR11(2849-2856).
IEEE DOI 1106
BibRef

Kulkarni, N.[Naveen], Li, B.X.[Bao-Xin],
Discriminative affine sparse codes for image classification,
CVPR11(1609-1616).
IEEE DOI 1106
BibRef

Yu, K.[Kai], Lin, Y.Q.[Yuan-Qing], Lafferty, J.[John],
Learning image representations from the pixel level via hierarchical sparse coding,
CVPR11(1713-1720).
IEEE DOI 1106
BibRef

Bespalov, D.[Dmitriy], Dahl, A.L.[Anders Lindbjerg], Bai, B.[Bing], Shokoufandeh, A.[Ali],
On Inferring Image Label Information Using Rank Minimization for Supervised Concept Embedding,
SCIA11(103-113).
Springer DOI 1105
BibRef

Wu, L.[Lina], Luo, S.W.[Si-Wei], Sun, W.[Wei], Zheng, X.[Xiang],
Integrating ILSR to Bag-of-Visual Words Model Based on Sparse Codes of SIFT Features Representations,
ICPR10(4283-4286).
IEEE DOI 1008
Implicit local spatial relationship. ILSR Sparse codes of SIFT features. BibRef

Han, X.H.[Xian-Hua], Chen, Y.W.[Yen-Wei], Ruan, X.[Xiang],
Image recognition by learned linear subspace of combined bag-of-features and low-level features,
ICIP10(1049-1052).
IEEE DOI 1009
BibRef
And:
Image Categorization by Learned Nonlinear Subspace of Combined Visual-Words and Low-Level Features,
ICPR10(3037-3040).
IEEE DOI 1008
Object and scene classes. BibRef

Zhan, Y.B.[Yu-Bin], Yin, J.P.[Jian-Ping],
Cluster Preserving Embedding,
ICPR10(621-624).
IEEE DOI 1008
BibRef

Przelaskowski, A.[Artur],
The Role of Sparse Data Representation in Semantic Image Understanding,
ICCVG10(I: 69-80).
Springer DOI 1009
BibRef

Huang, J.B.[Jia-Bin], Yang, M.H.[Ming-Hsuan],
Fast sparse representation with prototypes,
CVPR10(3618-3625).
IEEE DOI 1006
BibRef

Liu, Y.[Yanan], Wu, F.[Fei], Zhang, Z.H.[Zhi-Hua], Zhuang, Y.T.[Yue-Ting], Yan, S.C.[Shui-Cheng],
Sparse representation using nonnegative curds and whey,
CVPR10(3578-3585).
IEEE DOI 1006
Set of sparse and nonnegative representations. Then incorporate these into a sparse representation. BibRef

Nakashizuka, M.[Makoto], Nishiura, H.[Hidenari], Iiguni, Y.[Youji],
Sparse image representations with shift-invariant tree-structured dictionaries,
ICIP09(2145-2148).
IEEE DOI 0911
BibRef

Gong, D.[Dian], Zhao, X.M.[Xue-Mei], Yang, Q.[Qiong],
Sparse Non-negative Pattern Learning for image representation,
ICIP08(981-984).
IEEE DOI 0810
Patterns are learned, features are extracted then used for representation. BibRef

Tsai, Y.T.[Yun-Ta], Wang, Q.[Quan], You, S.[Suya],
CDIKP: A highly-compact local feature descriptor,
ICPR08(1-4).
IEEE DOI 0812
SIFT combined with projection BibRef

Heiler, M.[Matthias], Schnörr, C.[Christoph],
Controlling Sparseness in Non-negative Tensor Factorization,
ECCV06(I: 56-67).
Springer DOI 0608
BibRef

Heiler, M.[Matthias], Schnörr, C.[Christoph],
Reverse-Convex Programming for Sparse Image Codes,
EMMCVPR05(600-616).
Springer DOI 0601
BibRef
And:
Learning Non-Negative Sparse Image Codes by Convex Programming,
ICCV05(II: 1667-1674).
IEEE DOI 0510
Aim to preserve local structure, unlike PCA. See also Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values. BibRef

Polak, S.[Simon], Shashua, A.[Amnon],
The Semi-explicit Shape Model for Multi-object Detection and Classification,
ECCV10(II: 336-349).
Springer DOI 1009
BibRef

Shashua, A.[Amnon], Zass, R.[Ron], Hazan, T.[Tamir],
Multi-way Clustering Using Super-Symmetric Non-negative Tensor Factorization,
ECCV06(IV: 595-608).
Springer DOI 0608
See also Probabilistic graph and hypergraph matching. BibRef

Hazan, T.[Tamir], Polak, S.[Simon], Shashua, A.[Amnon],
Sparse Image Coding Using a 3D Non-Negative Tensor Factorization,
ICCV05(I: 50-57).
IEEE DOI 0510
Generate descriptions (e.g. bases) of images. BibRef

Haasdonk, B., Halawani, A., Burkhardt, H.,
Adjustable Invariant Features by Partial Haar-Integration,
ICPR04(II: 769-774).
IEEE DOI 0409
BibRef

Molina-Gamez, M., Subirana-Vilanova, J.B.,
Sparse Groups: A Polynomial Middle-Level Approach for Object Recognition,
ICPR96(I: 518-522).
IEEE DOI 9608
(Autonomous Univ. of Barcelona, E) BibRef

Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Other, Kernel Methods, Invariants .


Last update:Nov 11, 2017 at 13:31:57