14.1.4.3 Transfer Learning from Other Classes

Yang, C.Y.[Chun-Yu], Zhou, J.[Jie],
Non-stationary data sequence classification using online class priors estimation,
PR(41), No. 8, August 2008, pp. 2656-2664.
Elsevier DOI 0805
Concept drift; Online classification; EM BibRef

Zhang, Z.H.[Zhi-Hao], Zhou, J.[Jie],
Transfer estimation of evolving class priors in data stream classification,
PR(43), No. 9, September 2010, pp. 3151-3161.
Elsevier DOI 1006
Concept drift; Transfer learning; Prior estimation BibRef

Gao, X.B.[Xin-Bo], Wang, X.M.[Xiu-Mei], Li, X.L.[Xue-Long], Tao, D.C.[Da-Cheng],
Transfer latent variable model based on divergence analysis,
PR(44), No. 10-11, October-November 2011, pp. 2358-2366.
Elsevier DOI 1101
Dimensionality reduction; Latent variable model; Transfer learning; Bregman divergence BibRef

Pang, J., Huang, Q., Yan, S., Jiang, S., Qin, L.,
Transferring Boosted Detectors Towards Viewpoint and Scene Adaptiveness,
IP(20), No. 5, May 2011, pp. 1388-1400.
IEEE DOI 1104
Training set isn't exactly the same as test data. BibRef

di Carlo, S., Falasconi, M., Sanchez, E., Scionti, A., Squillero, G., Tonda, A.,
Increasing pattern recognition accuracy for chemical sensing by evolutionary based drift compensation,
PRL(32), No. 13, 1 October 2011, pp. 1594-1603.
Elsevier DOI 1109
Sensor drift; Evolutionary strategy; Classification systems BibRef

Gonçalves, Jr., P.M.[Paulo Mauricio], Maior de Barros, R.S.[Roberto Souto],
RCD: A recurring concept drift framework,
PRL(34), No. 9, July 2013, pp. 1018-1025.
Elsevier DOI 1305
Data streams; Concept drift; Recurring contexts; On-line learning; Multivariate non-parametric statistical test BibRef

Salakhutdinov, R.[Ruslan], Tenenbaum, J.B.[Joshua B.], Torralba, A.B.[Antonio B.],
Learning with Hierarchical-Deep Models,
PAMI(35), No. 8, 2013, pp. 1958-1971.
IEEE DOI 1307
BibRef
Earlier: A1, A3, A2:
Learning to share visual appearance for multiclass object detection,
CVPR11(1481-1488).
IEEE DOI 1106
Bayesian methods; Deep networks. Rare objects "borrow" statistical info from related common objects. Learn hierarchy of objects. BibRef

Lin, D.[Di], An, X.[Xing], Zhang, J.[Jian],
Double-bootstrapping source data selection for instance-based transfer learning,
PRL(34), No. 11, 1 August 2013, pp. 1279-1285.
Elsevier DOI 1306
Transfer learning; Instance-based transfer learning; Source data selection; Bagging BibRef

Varga, R., Nedevschi, S.,
Label Transfer by Measuring Compactness,
IP(22), No. 12, 2013, pp. 4711-4723.
IEEE DOI 1312
feature extraction BibRef

Li, Q.[Qing], Chen, X.[Xiaowu], Song, Y.[Yafei], Zhang, Y., Jin, X.[Xin], Zhao, Q.P.[Qin-Ping],
Geodesic Propagation for Semantic Labeling,
IP(23), No. 11, November 2014, pp. 4812-4825.
IEEE DOI 1410
BibRef
Earlier: A2, A1, A3, A5, A6, Only:
Supervised Geodesic Propagation for Semantic Label Transfer,
ECCV12(III: 553-565).
Springer DOI 1210
Image color analysis BibRef

Khamis, S.[Sameh], Lampert, C.H.[Christoph H.],
CoConut: Co-Classification with Output Space Regularization,
BMVC14(xx-yy).
HTML Version. 1410
Jointly classifying multiple, otherwise independent, data samples. BibRef

Fang, M.[Min], Guo, Y.[Yong], Zhang, X.S.[Xiao-Song], Li, X.[Xiao],
Multi-source transfer learning based on label shared subspace,
PRL(51), No. 1, 2015, pp. 101-106.
Elsevier DOI 1412
Transfer learning BibRef

Sun, C.[Chao], Bao, B.K.[Bing-Kun], Xu, C.S.[Chang-Sheng],
Knowing Verb From Object: Retagging With Transfer Learning on Verb-Object Concept Images,
MultMed(17), No. 10, October 2015, pp. 1747-1759.
IEEE DOI 1511
Bayes methods BibRef

Xu, Y., Fang, X., Wu, J., Li, X., Zhang, D.,
Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation,
IP(25), No. 2, February 2016, pp. 850-863.
IEEE DOI 1601
Adaptation models BibRef

Deng, C., Tang, X., Yan, J., Liu, W., Gao, X.,
Discriminative Dictionary Learning With Common Label Alignment for Cross-Modal Retrieval,
MultMed(18), No. 2, February 2016, pp. 208-218.
IEEE DOI 1601
Correlation BibRef

Mudunuri, S.P.[Sivaram Prasad], Biswas, S.[Soma],
A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching,
PRL(71), No. 1, 2016, pp. 38-44.
Elsevier DOI 1602
Face recognition BibRef

Mandal, D., Biswas, S.[Soma],
Generalized Coupled Dictionary Learning Approach With Applications to Cross-Modal Matching,
IP(25), No. 8, August 2016, pp. 3826-3837.
IEEE DOI 1608
Correlation BibRef

Das, N., Mandal, D., Biswas, S.[Soma],
Simultaneous Semi-Coupled Dictionary Learning for Matching in Canonical Space,
IP(26), No. 8, August 2017, pp. 3995-4004.
IEEE DOI 1707
BibRef
Earlier:
Simultaneous Semi-Coupled Dictionary Learning for Matching RGBD Data,
Biometrics16(243-251)
IEEE DOI 1612
computer vision, image matching, image representation, Mahalanobis metric, canonical representation, canonical space, computer vision, cross-modal recognition, simultaneous semicoupled dictionary learning, sparse coefficients, Computer vision, Couplings, Dictionaries, Linear programming, Measurement, Testing, Training, Cross-modal matching, RGBD data, audio-image data, privileged information, text-image, data BibRef

An, T.H.[Taeg-Hyun], Hong, K.S.[Ki-Sang],
Label transfer via sparse representation,
PRL(70), No. 1, 2016, pp. 1-7.
Elsevier DOI 1602
Scene parsing BibRef

Zhang, L.[Lei], Zuo, W.M.[Wang-Meng], Zhang, D.,
LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation,
IP(25), No. 3, March 2016, pp. 1177-1191.
IEEE DOI 1602
Big Data BibRef

Zhou, S.[Shuang], Smirnov, E.[Evgueni], Schoenmakers, G.[Gijs], Driessens, K.[Kurt], Peeters, R.[Ralf],
Testing exchangeability for transfer decision,
PRL(88), No. 1, 2017, pp. 64-71.
Elsevier DOI 1703
Instance-transfer learning BibRef

Shoeleh, F.[Farzaneh], Asadpour, M.[Masoud],
Graph based skill acquisition and transfer Learning for continuous reinforcement learning domains,
PRL(87), No. 1, 2017, pp. 104-116.
Elsevier DOI 1703
Reinforcement learning BibRef

Wang, J.[Jie], Luo, C.[Chang], Huang, H.Q.[Han-Qiao], Zhao, H.Z.[Hui-Zhen], Wang, S.Q.[Shi-Qiang],
Transferring Pre-Trained Deep CNNs for Remote Scene Classification with General Features Learned from Linear PCA Network,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Qi, G.J., Liu, W., Aggarwal, C., Huang, T.,
Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes,
PAMI(39), No. 7, July 2017, pp. 1360-1373.
IEEE DOI 1706
Bridges, Noise measurement, Semantics, Training, Transfer functions, Videos, Visualization, Multimodal analysis, image classification, intermodal and intramodal label transfers (I2LT), zero-shot, learning BibRef

Wang, J.[Jun], Wang, G.Q.[Guo-Qing], Li, L.[Leida],
Image Pattern Similarity Index and Its Application to Task-Specific Transfer Learning,
IEICE(E100-D), No. 12, December 2017, pp. 3032-3035.
WWW Link. 1712
BibRef

Gao, N.N.[Neng-Neng], Huang, S.J.[Sheng-Jun], Yan, Y.F.[Yi-Fan], Chen, S.C.[Song-Can],
Cross modal similarity learning with active queries,
PR(75), No. 1, 2018, pp. 214-222.
Elsevier DOI 1712
Active learning BibRef

Zhang, B.C.[Bao-Chang], Perina, A.[Alessandro], Li, C.[Ce], Ye, Q.X.[Qi-Xiang], Murino, V.[Vittorio], Del Bue, A.[Alessio],
Manifold constraint transfer for visual structure-driven optimization,
PR(77), 2018, pp. 87-98.
Elsevier DOI 1802
Manifold, Transfer learning, Alternating direction method of multipliers, Object tracking, Object categorization BibRef

Kumar, S.[Suren], Dhiman, V.[Vikas], Koch, P.A.[Parker A.], Corso, J.J.[Jason J.],
Learning Compositional Sparse Bimodal Models,
PAMI(40), No. 5, May 2018, pp. 1032-1044.
IEEE DOI 1804
Transfer from, e.g., red triangles/blue squares to red squares/blue triangles. Dictionaries, Encoding, Poles and towers, Robot sensing systems, Semantics, Visualization, Multimodal learning, tabletop robotics BibRef

Zheng, F.[Feng], Tang, Y.[Yi], Shao, L.[Ling],
Hetero-Manifold Regularisation for Cross-Modal Hashing,
PAMI(40), No. 5, May 2018, pp. 1059-1071.
IEEE DOI 1804
Data models, Euclidean distance, Hamming distance, Manifolds, Semantics, Support vector machines, Training, Cross-modal hashing, manifold regularisation BibRef

Zhu, F.[Fan], Shao, L.[Ling], Tang, J.[Jun],
Boosted Cross-Domain Categorization,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Chang, H.[Hang], Han, J.[Ju], Zhong, C.[Cheng], Snijders, A.M.[Antoine M.], Mao, J.H.[Jian-Hua],
Unsupervised Transfer Learning via Multi-Scale Convolutional Sparse Coding for Biomedical Applications,
PAMI(40), No. 5, May 2018, pp. 1182-1194.
IEEE DOI 1804
Biological neural networks, Convolutional codes, Encoding, Feature extraction, Knowledge engineering, Training, sharable information BibRef

Peng, P.X.[Pei-Xi], Tian, Y.H.[Yong-Hong], Xiang, T.[Tao], Wang, Y.W.[Yao-Wei], Pontil, M.[Massimiliano], Huang, T.J.[Tie-Jun],
Joint Semantic and Latent Attribute Modelling for Cross-Class Transfer Learning,
PAMI(40), No. 7, July 2018, pp. 1625-1638.
IEEE DOI 1806
Adaptation models, Computational modeling, Data models, Dictionaries, Semantics, Training, Visualization, Attribute learning, zero-shot learning BibRef

Guo, X.[Xin], Wang, S.[Song], Tie, Y.[Yun], Qi, L.[Lin], Guan, L.[Ling],
Joint intermodal and intramodal correlation preservation for semi-paired learning,
PR(81), 2018, pp. 36-49.
Elsevier DOI 1806
Semi-paired learning, Canonical correlation analysis, Clustering BibRef

Shi, Q., Liu, X., Huang, X.,
An Active Relearning Framework for Remote Sensing Image Classification,
GeoRS(56), No. 6, June 2018, pp. 3468-3486.
IEEE DOI 1806
Adaptation models, Convergence, Feature extraction, Remote sensing, Spectral analysis, Training, Uncertainty, Active learning (AL), relearning BibRef

Han, W.[Wei], Feng, R.[Ruyi], Wang, L.Z.[Li-Zhe], Cheng, Y.F.[Ya-Fan],
A semi-supervised generative framework with deep learning features for high-resolution remote sensing image scene classification,
PandRS(145), 2018, pp. 23-43.
Elsevier DOI 1810
Scene classification, Deep learning, Self-label, High resolution remote sensing images BibRef

Ding, Z., Fu, Y.,
Dual Low-Rank Decompositions for Robust Cross-View Learning,
IP(28), No. 1, January 2019, pp. 194-204.
IEEE DOI 1810
Manifolds, Robustness, Feature extraction, Face, Task analysis, Data models, Sensors, Cross-view learning, low-rank modeling, graph embedding BibRef

Ma, Z.C.[Zhong-Chen], Chen, S.C.[Song-Can], Ma, D.[Di],
Heterogeneous multi-output classification by structured conditional risk minimization,
PRL(116), 2018, pp. 50-57.
Elsevier DOI 1812
Multi-output classification, Problem transformation, Output structures, Heterogeneity, Structured prediction BibRef

Duan, L.J.[Li-Juan], En, Q.[Qing], Qiao, Y.H.[Yuan-Hua], Cui, S.[Song], Qing, L.Y.[Lai-Yun],
Deep feature representation based on privileged knowledge transfer,
PRL(119), 2019, pp. 62-70.
Elsevier DOI 1902
Feature representation, Privileged knowledge transfer, Deep neural network, Multi-object retrieval BibRef

Shi, Q.[Qian], Zhang, Y.[Yipeng], Liu, X.P.[Xiao-Ping], Zhao, K.[Kefei],
Regularised transfer learning for hyperspectral image classification,
IET-CV(13), No. 2, March 2019, pp. 188-193.
DOI Link 1902
BibRef

Tang, X.Y.[Xin-Yao], Du, B.[Bo], Huang, J.Z.[Jian-Zhong], Wang, Z.[Zengmao], Zhang, L.F.[Le-Fei],
On combining active and transfer learning for medical data classification,
IET-CV(13), No. 2, March 2019, pp. 194-205.
DOI Link 1902
BibRef

Luo, Y.[Yong], Wen, Y.G.[Yong-Gang], Liu, T.L.[Tong-Liang], Tao, D.C.[Da-Cheng],
Transferring Knowledge Fragments for Learning Distance Metric from a Heterogeneous Domain,
PAMI(41), No. 4, April 2019, pp. 1013-1026.
IEEE DOI 1903
Measurement, Task analysis, Face, Visualization, Feature extraction, Training, Pattern recognition, Transfer learning, nonlinear BibRef

Deng, C.[Cheng], Xue, Y.M.[Yu-Meng], Liu, X.L.[Xiang-Long], Li, C.[Chao], Tao, D.C.[Da-Cheng],
Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model for Hyperspectral Image Classification,
GeoRS(57), No. 3, March 2019, pp. 1741-1754.
IEEE DOI 1903
feature extraction, geophysical image processing, image classification, learning (artificial intelligence), transfer learning (TL) BibRef

Ji, R.R.[Rong-Rong], Gao, Y.[Yue], Hong, R.C.[Ri-Chang], Liu, Q.[Qiong], Tao, D.C.[Da-Cheng], Li, X.L.[Xue-Long],
Spectral-Spatial Constraint Hyperspectral Image Classification,
GeoRS(52), No. 3, March 2014, pp. 1811-1824.
IEEE DOI 1403
hyperspectral imaging BibRef

Luo, F.[Fulin], Du, B.[Bo], Zhang, L.P.[Liang-Pei], Zhang, L.F.[Le-Fei], Tao, D.C.[Da-Cheng],
Feature Learning Using Spatial-Spectral Hypergraph Discriminant Analysis for Hyperspectral Image,
Cyber(49), No. 7, July 2019, pp. 2406-2419.
IEEE DOI 1905
Feature extraction, Laplace equations, Learning systems, Cybernetics, Hyperspectral imaging, Image reconstruction, spatial-spectral information BibRef

Basavaraju, S.[Sathisha], Gaj, S.[Sibaji], Sur, A.[Arijit],
Object Memorability Prediction using Deep Learning: Location and Size Bias,
JVCIR(59), 2019, pp. 117-127.
Elsevier DOI 1903
Object Memorability, Deep Learning, Transfer Learning BibRef

Ye, R.[Rui], Dai, Q.[Qun], Li, M.[MeiLing],
A hybrid transfer learning algorithm incorporating TrSVM with GASEN,
PR(92), 2019, pp. 192-202.
Elsevier DOI 1905
Transfer learning, Ensemble selection, Genetic Algorithm based Selective Ensemble algorithm (GASEN), Transfer Learning algorithm incorporating TrSVM with GASEN (TrGASVM) BibRef

Wang, C.[Chao], Tuo, H.[Hongya], Wang, J.X.[Jie-Xin], Qiao, L.F.[Ling-Feng],
Discriminative transfer learning via local and global structure preservation,
SIViP(13), No. 4, June 2019, pp. 753-760.
Springer DOI 1906
BibRef

Zhang, J.[Jing], Li, W.Q.[Wan-Qing], Ogunbona, P.[Philip], Xu, D.[Dong],
Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition: A Problem-Oriented Perspective,
Surveys(51), No. 1, February 2019, pp. Article No 7.
DOI Link 1906
Survey, Transfer Learning. BibRef

Xue, S.[Shan], Lu, J.[Jie], Zhang, G.Q.[Guang-Quan],
Cross-domain network representations,
PR(94), 2019, pp. 135-148.
Elsevier DOI 1906
Network representation, Transfer learning, Random walk, Information network, Unsupervised learning, Feature learning BibRef

Yu, X.[Xu], Jiang, F.[Feng], Du, J.W.[Jun-Wei], Gong, D.W.[Dun-Wei],
A cross-domain collaborative filtering algorithm with expanding user and item features via the latent factor space of auxiliary domains,
PR(94), 2019, pp. 96-109.
Elsevier DOI 1906
Cross-domain collaborative filtering, Feature expansion, Funk-SVD decomposition, Classification, Latent factor space BibRef

Rostami, M.[Mohammad], Kolouri, S.[Soheil], Eaton, E.[Eric], Kim, K.[Kyungnam],
Deep Transfer Learning for Few-Shot SAR Image Classification,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Hong, D., Yokoya, N., Chanussot, J., Zhu, X.X.,
CoSpace: Common Subspace Learning From Hyperspectral-Multispectral Correspondences,
GeoRS(57), No. 7, July 2019, pp. 4349-4359.
IEEE DOI 1907
Hyperspectral imaging, Optimization, Satellites, Earth, Manifolds, Common subspace learning (CoSpace), cross-modality learning, remote sensing BibRef

Chen, W., Hsu, T.H., Tsai, Y.H., Chen, M., Wang, Y.F.,
Transfer Neural Trees: Semi-Supervised Heterogeneous Domain Adaptation and Beyond,
IP(28), No. 9, Sep. 2019, pp. 4620-4633.
IEEE DOI 1908
image classification, learning (artificial intelligence), pattern classification, trees (mathematics), zero-shot learning BibRef

Tan, M.[Min], Yu, J.[Jun], Zhang, H.Y.[Hong-Yuan], Rui, Y.[Yong], Tao, D.C.[Da-Cheng],
Image Recognition by Predicted User Click Feature With Multidomain Multitask Transfer Deep Network,
IP(28), No. 12, December 2019, pp. 6047-6062.
IEEE DOI 1909
Image recognition, Task analysis, Visualization, Predictive models, Adaptation models, Correlation, Computational modeling, word embedding BibRef

Yan, C., Li, L., Zhang, C., Liu, B., Zhang, Y., Dai, Q.,
Cross-Modality Bridging and Knowledge Transferring for Image Understanding,
MultMed(21), No. 10, October 2019, pp. 2675-2685.
IEEE DOI 1910
feature extraction, image classification, image representation, learning (artificial intelligence), multimedia systems, knowledge transferring BibRef

Li, X.H.[Xu-Hong], Grandvalet, Y.[Yves], Davoine, F.[Franck],
A baseline regularization scheme for transfer learning with convolutional neural networks,
PR(98), 2020, pp. 107049.
Elsevier DOI 1911
Transfer learning, Regularization, Convolutional networks BibRef

Sanodiya, R.K.[Rakesh Kumar], Mathew, J.[Jimson],
A novel unsupervised Globality-Locality Preserving Projections in transfer learning,
IVC(90), 2019, pp. 103802.
Elsevier DOI 1912
Discriminant analysis, Transfer learning, Domain adaptation, Manifold, Classification, Unsupervised learning, Dimensionality reduction BibRef

Han, N., Wu, J., Fang, X., Xie, S., Zhan, S., Xie, K., Li, X.,
Latent Elastic-Net Transfer Learning,
IP(29), 2020, pp. 2820-2833.
IEEE DOI 2001
Transfer learning, elastic-net, source domain, target domain, machine learning BibRef

Pires de Lima, R.[Rafael], Marfurt, K.[Kurt],
Convolutional Neural Network for Remote-Sensing Scene Classification: Transfer Learning Analysis,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link 2001
BibRef

Zhang, B., Yang, W., Wang, Z., Zhuo, L., Han, J., Zhen, X.,
The Structure Transfer Machine: Theory and Applications,
IP(29), 2020, pp. 2889-2902.
IEEE DOI 2002
Manifolds, Deep learning, Training, Probabilistic logic, Object tracking, Task analysis, Transfer learning, learning theory BibRef

Das, D., Lee, C.S.G.,
A Two-Stage Approach to Few-Shot Learning for Image Recognition,
IP(29), 2020, pp. 3336-3350.
IEEE DOI 2002
Transfer learning, convolutional neural network, few-shot learning, image classification BibRef

Gholenji, E.[Elahe], Tahmoresnezhad, J.[Jafar],
Joint local and statistical discriminant learning via feature alignment,
SIViP(14), No. 3, April 2020, pp. 609-616.
Springer DOI 2004
Machine learning applied to unseen items. Domain shift. BibRef

Peng, Z., Zhang, W., Han, N., Fang, X., Kang, P., Teng, L.,
Active Transfer Learning,
CirSysVideo(30), No. 4, April 2020, pp. 1022-1036.
IEEE DOI 2004
Task analysis, Kernel, Bicycles, Linear programming, Machine learning, Training, Optimization, Negative transfer, information diversity BibRef

Bae, J.H.[Ji-Hoon], Yeo, D.[Doyeob], Yim, J.[Junho], Kim, N.S.[Nae-Soo], Pyo, C.S.[Cheol-Sig], Kim, J.[Junmo],
Densely Distilled Flow-Based Knowledge Transfer in Teacher-Student Framework for Image Classification,
IP(29), 2020, pp. 5698-5710.
IEEE DOI 2005
BibRef
Earlier: A2, A1, A5, A3, A4, A6:
Sequential Knowledge Transfer in Teacher-Student Framework Using Densely Distilled Flow-Based Information,
ICIP18(674-678)
IEEE DOI 1809
Knowledge transfer, Training, Computational modeling, Data mining, Optimization, Image classification, Computer architecture, residual network. Training, Data mining, Optimization, Image classification, Knowledge transfer, Computational modeling, Reliability, BibRef

Dong, R.M.[Run-Min], Li, C.[Cong], Fu, H.[Haohuan], Wang, J.[Jie], Li, W.[Weijia], Yao, Y.[Yi], Gan, L.[Lin], Yu, L.[Le], Gong, P.[Peng],
Improving 3-m Resolution Land Cover Mapping through Efficient Learning from an Imperfect 10-m Resolution Map,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Liu, W., Qin, R.,
A MultiKernel Domain Adaptation Method for Unsupervised Transfer Learning on Cross-Source and Cross-Region Remote Sensing Data Classification,
GeoRS(58), No. 6, June 2020, pp. 4279-4289.
IEEE DOI 2005
Domain adaptation (DA), image classification, remote sensing, stable index, transfer learning (TL), unsupervised learning BibRef

Lu, Y.[Ying], Luo, L.[Lingkun], Huang, D.[Di], Wang, Y.H.[Yun-Hong], Chen, L.M.[Li-Ming],
Knowledge Transfer in Vision Recognition: A Survey,
Surveys(53), No. 2, April 2020, pp. xx-yy.
DOI Link 2007
vision recognition, computer vision, transfer learning, Knowledge transfer, machine learning BibRef

Lamb, A.[Alex], Ozair, S.[Sherjil], Verma, V.[Vikas], Ha, D.[David],
SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks,
WACV20(952-961)
IEEE DOI 2006
Domain transfer applied to sketch recognition. Result are not great. Training, Task analysis, Cats, Dogs, Automobiles, Perturbation methods, Ear BibRef

Li, J., Xu, Z., Wang, Y., Zhao, Q., Kankanhalli, M.S.,
GradMix: Multi-source Transfer across Domains and Tasks,
WACV20(3008-3016)
IEEE DOI 2006
Task analysis, Training, Adaptation models, Silicon, Computer vision, Optimization, Training data BibRef

Bi, S.[Sai], Sunkavalli, K.[Kalyan], Perazzi, F.[Federico], Shechtman, E.[Eli], Kim, V.[Vladimir], Ramamoorthi, R.[Ravi],
Deep CG2Real: Synthetic-to-Real Translation via Image Disentanglement,
ICCV19(2730-2739)
IEEE DOI 2004
Train on synthetic. image processing, learning (artificial intelligence), two-stage pipeline, improved CycleGAN network, Training BibRef

Tran, A.T.[Anh Tuan], Nguyen, C.[Cuong], Hassner, T.[Tal],
Transferability and Hardness of Supervised Classification Tasks,
ICCV19(1395-1405)
IEEE DOI 2004
entropy, face recognition, image classification, learning (artificial intelligence), object recognition, Computational modeling BibRef

Wu, Y.W.[Yuan-Wei], Zhang, Z.M.[Zi-Ming], Wang, G.H.[Guang-Hui],
Unsupervised Deep Feature Transfer for Low Resolution Image Classification,
RLQ19(1065-1069)
IEEE DOI 2004
data structures, feature extraction, image classification, image enhancement, image resolution, neural nets, low resolution image classificatin BibRef

Li, K., Zhang, Y., Li, K., Li, Y., Fu, Y.,
Attention Bridging Network for Knowledge Transfer,
ICCV19(5197-5206)
IEEE DOI 2004
image segmentation, learning (artificial intelligence), neural nets, pattern classification, classification network, Knowledge transfer BibRef

Kuen, J., Perazzi, F., Lin, Z., Zhang, J., Tan, Y.,
Scaling Object Detection by Transferring Classification Weights,
ICCV19(6043-6052)
IEEE DOI 2004
feature extraction, genomics, image classification, information retrieval, learning (artificial intelligence), Knowledge engineering BibRef

Huang, H., Jain, V., Mehta, H., Ku, A., Magalhaes, G., Baldridge, J., Ie, E.,
Transferable Representation Learning in Vision-and-Language Navigation,
ICCV19(7403-7412)
IEEE DOI 2004
computer vision, image sequences, learning (artificial intelligence), Length measurement BibRef

Han, K., Vedaldi, A., Zisserman, A.,
Learning to Discover Novel Visual Categories via Deep Transfer Clustering,
ICCV19(8400-8408)
IEEE DOI 2004
image classification, learning (artificial intelligence), object recognition, pattern clustering, known classes, Dogs BibRef

Durall, R., Pfreundt, F., Keuper, J.,
Semi Few-Shot Attribute Translation,
IVCNZ19(1-8)
IEEE DOI 2004
image processing, learning (artificial intelligence), semifew-shot attribute translation, image-to-image translation, generative transfer learning BibRef

Iqbal, A., Richard, A., Gall, J.,
Enhancing Temporal Action Localization with Transfer Learning from Action Recognition,
CoView19(1533-1540)
IEEE DOI 2004
feature extraction, image classification, image motion analysis, image segmentation, image sequences, inference mechanisms, Action Detection BibRef

Liu, B., Wu, Z., Hu, H., Lin, S.,
Deep Metric Transfer for Label Propagation with Limited Annotated Data,
MDALC19(1317-1326)
IEEE DOI 2004
Code, Learning.
WWW Link. image annotation, object recognition, unsupervised learning, deep metric transfer, limited annotated data, object class, self supervised learning BibRef

Jakubovitz, D., Rodrigues, M.R.D., Giryes, R.,
Lautum Regularization for Semi-Supervised Transfer Learning,
SDL-CV19(763-767)
IEEE DOI 2004
information theory, learning (artificial intelligence), neural nets, source dataset, deep neural network, Information Theory BibRef

Cicek, S., Soatto, S.,
Unsupervised Domain Adaptation via Regularized Conditional Alignment,
ICCV19(1416-1425)
IEEE DOI 2004
pattern classification, statistical distributions, unsupervised learning, classifier performance, Neural networks BibRef

Dwivedi, K.[Kshitij], Roig, G.[Gemma],
Representation Similarity Analysis for Efficient Task Taxonomy and Transfer Learning,
CVPR19(12379-12388).
IEEE DOI 2002
BibRef

Wang, Z.[Zirui], Dai, Z.[Zihang], Poczos, B.[Barnabas], Carbonell, J.[Jaime],
Characterizing and Avoiding Negative Transfer,
CVPR19(11285-11294).
IEEE DOI 2002
BibRef

Ahn, S.S.[Sung-Soo], Hu, S.X.[Shell Xu], Damianou, A.[Andreas], Lawrence, N.D.[Neil D.], Dai, Z.W.[Zhen-Wen],
Variational Information Distillation for Knowledge Transfer,
CVPR19(9155-9163).
IEEE DOI 2002
BibRef

Herath, S.[Samitha], Harandi, M.[Mehrtash], Fernando, B.[Basura], Nock, R.[Richard],
Min-Max Statistical Alignment for Transfer Learning,
CVPR19(9280-9289).
IEEE DOI 2002
BibRef

Chen, Y.C.[Yun-Chun], Lin, Y.Y.[Yen-Yu], Yang, M.H.[Ming-Hsuan], Huang, J.B.[Jia-Bin],
CrDoCo: Pixel-Level Domain Transfer With Cross-Domain Consistency,
CVPR19(1791-1800).
IEEE DOI 2002
BibRef

Gong, R.[Rui], Li, W.[Wen], Chen, Y.H.[Yu-Hua], Van Gool, L.J.[Luc J.],
DLOW: Domain Flow for Adaptation and Generalization,
CVPR19(2472-2481).
IEEE DOI 2002
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Li, Y.S.[Yun-Sheng], Vasconcelos, N.M.[Nuno M.],
Efficient Multi-Domain Learning by Covariance Normalization,
CVPR19(5419-5428).
IEEE DOI 2002
BibRef

Oza, P.[Poojan], Patel, V.M.[Vishal M.],
C2AE: Class Conditioned Auto-Encoder for Open-Set Recognition,
CVPR19(2302-2311).
IEEE DOI 2002
BibRef

Essich, M.[Michael], Ludl, D.[Dennis], Gulde, T.[Thomas], Curio, C.[Cristóbal],
Learning to Translate Between Real World and Simulated 3D Sensors While Transferring Task Models,
3DV19(681-689)
IEEE DOI 1911
Real data not like trained data Sensors, Data models, Task analysis, Adaptation models, Training, Character Animation BibRef

Minami, S.[Soma], Yamashita, T.[Takayoshi], Fujiyoshi, H.[Hironobu],
Gradual Sampling Gate for Bidirectional Knowledge Distillation,
MVA19(1-6)
DOI Link 1911
Transfer knowledge from large pre-trained network to smaller one. data compression, learning (artificial intelligence), neural nets, gradual sampling gate, Power markets BibRef

Coors, B.[Benjamin], Condurache, A.P.[Alexandru Paul], Geiger, A.[Andreas],
NoVA: Learning to See in Novel Viewpoints and Domains,
3DV19(116-125)
IEEE DOI 1911
Adaptation models, Task analysis, Estimation, Semantics, Image segmentation, Cameras, Geometry, Novel Viewpoint Adaptation, Viewpoint Invariance BibRef

Bao, Y., Li, Y., Huang, S., Zhang, L., Zheng, L., Zamir, A., Guibas, L.J.[Leonidas J.],
An Information-Theoretic Approach to Transferability in Task Transfer Learning,
ICIP19(2309-2313)
IEEE DOI 1910
Task transfer learning, Transferability, H-Score, Image recognition & classification BibRef

Zhu, Y.[Yi], Xue, J.[Jia], Newsam, S.[Shawn],
Gated Transfer Network for Transfer Learning,
ACCV18(IV:354-369).
Springer DOI 1906
BibRef

Kim, J.[Jaekyum], Koh, J.[Junho], Kim, Y.[Yecheol], Choi, J.[Jaehyung], Hwang, Y.[Youngbae], Choi, J.W.[Jun Won],
Robust Deep Multi-modal Learning Based on Gated Information Fusion Network,
ACCV18(IV:90-106).
Springer DOI 1906
BibRef

Zhong, Y.[Yang], Li, V.[Vladimir], Okada, R.[Ryuzo], Maki, A.[Atsuto],
Target Aware Network Adaptation for Efficient Representation Learning,
CEFR-LCV18(IV:450-467).
Springer DOI 1905
Finding the CNN that works. BibRef

Okatani, T.[Takayuki], Liu, X.[Xing], Suganuma, M.[Masanori],
Improving Generalization Ability of Deep Neural Networks for Visual Recognition Tasks,
CCIW19(3-13).
Springer DOI 1905
BibRef

Sawatzky, J.[Johann], Garbade, M.[Martin], Gall, J.[Juergen],
Ex Paucis Plura: Learning Affordance Segmentation from Very Few Examples,
GCPR18(169-184).
Springer DOI 1905
Use existing annotated datasets to annotate new ones (reduce what needs more work). BibRef

Sayed, N.[Nawid], Brattoli, B.[Biagio], Ommer, B.[Björn],
Cross and Learn: Cross-Modal Self-supervision,
GCPR18(228-243).
Springer DOI 1905
BibRef

Rahman, M.M.[Mohammad Mahfujur], Fookes, C.[Clinton], Baktashmotlagh, M.[Mahsa], Sridharan, S.[Sridha],
Multi-Component Image Translation for Deep Domain Generalization,
WACV19(579-588)
IEEE DOI 1904
image classification, learning (artificial intelligence), neural nets, protocols, protocol, synthetic images, Adaptation models BibRef

Chen, D., Liang, X., Wang, Y., Gao, W.,
Soft Transfer Learning via Gradient Diagnosis for Visual Relationship Detection,
WACV19(1118-1126)
IEEE DOI 1904
inference mechanisms, learning (artificial intelligence), object detection, optimisation, diverse language ambiguities, Dogs BibRef

Wang, T., Huan, J., Zhu, M.,
Instance-Based Deep Transfer Learning,
WACV19(367-375)
IEEE DOI 1904
computer vision, image classification, learning (artificial intelligence), Load modeling BibRef

Li, J.S.[Jian-Shu], Zhou, P.[Pan], Chen, Y.P.[Yun-Peng], Zhao, J.[Jian], Roy, S.[Sujoy], Yan, S.C.[Shui-Cheng], Feng, J.S.[Jia-Shi], Sim, T.[Terence],
Task Relation Networks,
WACV19(932-940)
IEEE DOI 1904
covariance matrices, learning (artificial intelligence), task analysis, task covariance modeling, Heuristic algorithms See also Estimation of Affective Level in the Wild with Multiple Memory Networks. BibRef

Zhang, Y.[Ying], Xiang, T.[Tao], Hospedales, T.M.[Timothy M.], Lu, H.C.[Hu-Chuan],
Deep Mutual Learning,
CVPR18(4320-4328)
IEEE DOI 1812
Training, Computational modeling, Task analysis, Supervised learning, Optimization, Entropy, Neural networks BibRef

Kundu, J.N.[Jogendra Nath], Uppala, P.K.[Phani Krishna], Pahuja, A.[Anuj], Babu, R.V.[R. Venkatesh],
AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation,
CVPR18(2656-2665)
IEEE DOI 1812
Task analysis, Estimation, Semantics, Adaptation models, Training, Predictive models. BibRef

Lee, K., He, X., Zhang, L., Yang, L.,
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise,
CVPR18(5447-5456)
IEEE DOI 1812
Noise measurement, Feature extraction, Training, Task analysis, Neural networks, Labeling, Manuals BibRef

Zamir, A.R., Sax, A., Shen, W., Guibas, L.J.[Leonidas J.], Malik, J., Savarese, S.,
Taskonomy: Disentangling Task Transfer Learning,
CVPR18(3712-3722)
IEEE DOI 1812
Task analysis, Computational modeling, Taxonomy, Dictionaries BibRef

Chen, S., Zhang, C., Dong, M.,
Coupled End-to-End Transfer Learning with Generalized Fisher Information,
CVPR18(4329-4338)
IEEE DOI 1812
Task analysis, Training, Decoding, Neural networks, Adaptation models, Image reconstruction, Feature extraction BibRef

Huang, X., Peng, Y.,
Deep Cross-Media Knowledge Transfer,
CVPR18(8837-8846)
IEEE DOI 1812
Media, Training, Correlation, Semantics, Adaptation models, Knowledge transfer, Computational modeling BibRef

Noroozi, M., Vinjimoor, A., Favaro, P., Pirsiavash, H.,
Boosting Self-Supervised Learning via Knowledge Transfer,
CVPR18(9359-9367)
IEEE DOI 1812
Task analysis, Computer architecture, Computational modeling, Training, Feature extraction, Data models, Measurement BibRef

Mormont, R., Geurts, P., Marée, R.,
Comparison of Deep Transfer Learning Strategies for Digital Pathology,
Microscopy18(2343-234309)
IEEE DOI 1812
Feature extraction, Task analysis, Biomedical imaging, Training, Support vector machines, Computer vision BibRef

Lu, W., Chung, F.,
A Deep Graphical Model for Layered Knowledge Transfer,
ICPR18(260-265)
IEEE DOI 1812
Task analysis, Dictionaries, Adaptation models, Inference algorithms, Graphical models, Training BibRef

Passalis, N., Tefas, A.,
Neural Network Knowledge Transfer using Unsupervised Similarity Matching,
ICPR18(716-721)
IEEE DOI 1812
a Receivers, Knowledge transfer, Training, Knowledge engineering, Neural networks, Computational modeling, Geometry BibRef

Wu, Y.X.[Yu-Xin], He, K.[Kaiming],
Group Normalization,
ECCV18(XIII: 3-19).
Springer DOI 1810
BibRef

Pan, X.G.[Xin-Gang], Luo, P.[Ping], Shi, J.P.[Jian-Ping], Tang, X.[Xiaoou],
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net,
ECCV18(II: 484-500).
Springer DOI 1810
Instance normalization and batch normalization for expanding domain. BibRef

Hou, S.H.[Sai-Hui], Pan, X.Y.[Xin-Yu], Loy, C.C.[Chen Change], Wang, Z.L.[Zi-Lei], Lin, D.H.[Da-Hua],
Lifelong Learning via Progressive Distillation and Retrospection,
ECCV18(III: 452-467).
Springer DOI 1810
BibRef

Huang, H.S.[Hao-Shuo], Huang, Q.X.[Qi-Xing], Krähenbühl, P.[Philipp],
Domain Transfer Through Deep Activation Matching,
ECCV18(XVI: 611-626).
Springer DOI 1810
BibRef

Tao, Q.Y.[Qing-Yi], Yang, H.[Hao], Cai, J.F.[Jian-Fei],
Zero-Annotation Object Detection with Web Knowledge Transfer,
ECCV18(XI: 387-403).
Springer DOI 1810
BibRef

Pintea, S.L.[Silvia L.], Liu, Y.[Yue], van Gemert, J.C.[Jan C.],
Recurrent Knowledge Distillation,
ICIP18(3393-3397)
IEEE DOI 1809
small network learns from larger network. Computational modeling, Memory management, Training, Color, Convolution, Road transportation, Knowledge distillation, recurrent layers BibRef

Paul, A.[Angshuman], Majumdar, A.[Angshul], Mukherjee, D.P.[Dipti Prasad],
Discriminative Autoencoder,
ICIP18(3049-3053)
IEEE DOI 1809
Minimization, Linear programming, Training, Encoding, Biomedical imaging, Decoding, Autoencoder, discriminative, cross-dataset BibRef

Inoue, T., Choudhury, S., De Magistris, G., Dasgupta, S.,
Transfer Learning from Synthetic to Real Images Using Variational Autoencoders for Precise Position Detection,
ICIP18(2725-2729)
IEEE DOI 1809
Lighting, Training, Task analysis, Robots, Decoding, Image color analysis, Cameras, deep learning, position detection, computer simulation BibRef

Liu, X., Wang, C., Hu, Y., Zeng, Z., Bai, J., Liao, G.,
Transfer Learning with Convolutional Neural Network for Early Gastric Cancer Classification on Magnifiying Narrow-Band Imaging Images,
ICIP18(1388-1392)
IEEE DOI 1809
Feature extraction, Task analysis, Computer architecture, Cancer, Training, Sensitivity, Convolutional neural networks, convolutional neural networks (CNNs) BibRef

Bai, T., Yang, J., Chen, J., Guo, X., Huang, X., Yao, Y.,
Double-Task Deep Q-Learning with Multiple Views,
CEFR-LCV17(1050-1058)
IEEE DOI 1802
Aerospace electronics, Cameras, Robot kinematics, Robot vision systems, Training BibRef

Chang, J.H.R.[J.H. Rick], Li, C.L.[Chun-Liang], Póczos, B.[Barnabás], Kumar, B.V.K.V.[B. V. K. Vijaya],
One Network to Solve Them All: Solving Linear Inverse Problems Using Deep Projection Models,
ICCV17(5889-5898)
IEEE DOI 1802
compressed sensing, image restoration, inverse problems, iterative methods, learning (artificial intelligence), Signal resolution BibRef

Li, D., Yang, Y., Song, Y.Z., Hospedales, T.M.,
Deeper, Broader and Artier Domain Generalization,
ICCV17(5543-5551)
IEEE DOI 1802
learning (artificial intelligence), DG alternatives, DG benchmark dataset, DG methods, benchmarks, Painting BibRef

Kim, K.I.[Kwang In], Tompkin, J.[James], Richardt, C.[Christian],
Predictor Combination at Test Time,
ICCV17(3573-3581)
IEEE DOI 1802
differential geometry, image denoising, learning (artificial intelligence), prediction theory, Training BibRef

Aygün, M., Aytar, Y., Ekenel, H.K.,
Exploiting Convolution Filter Patterns for Transfer Learning,
TASKCV17(2674-2680)
IEEE DOI 1802
Analytical models, Computer architecture, Convolution, Covariance matrices, Detectors, Training BibRef

Devi, V.S.[V. Sowmini], Padmanabhan, V.[Vineet], Pujari, A.K.[Arun K.],
A Matrix Factorization & Clustering Based Approach for Transfer Learning,
PReMI17(77-83).
Springer DOI 1711
BibRef

Aljundi, R.[Rahaf], Chakravarty, P.[Punarjay], Tuytelaars, T.[Tinne],
Expert Gate: Lifelong Learning with a Network of Experts,
CVPR17(7120-7129)
IEEE DOI 1711
Data models, Load modeling, Logic gates, Neural networks, Training, Training, data BibRef

Zhang, J., Li, W., Ogunbona, P.,
Joint Geometrical and Statistical Alignment for Visual Domain Adaptation,
CVPR17(5150-5158)
IEEE DOI 1711
Image recognition, Linear programming, Minimization, Pattern recognition, Training, Visualization BibRef

Ge, W., Yu, Y.,
Borrowing Treasures from the Wealthy: Deep Transfer Learning through Selective Joint Fine-Tuning,
CVPR17(10-19)
IEEE DOI 1711
Kernel, Machine learning, Neural networks, Training data, Visualization BibRef

Yim, J., Joo, D., Bae, J., Kim, J.,
A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning,
CVPR17(7130-7138)
IEEE DOI 1711
Feature extraction, Knowledge engineering, Knowledge transfer, Optimization, Training BibRef

Yu, L.J.[Liang-Jiang], Fan, G.L.[Guo-Liang],
Rare Class Oriented Scene Labeling Using CNN Incorporated Label Transfer,
ISVC16(I: 309-320).
Springer DOI 1701
BibRef

Gupta, S.[Saurabh], Hoffman, J.[Judy], Malik, J.[Jitendra],
Cross Modal Distillation for Supervision Transfer,
CVPR16(2827-2836)
IEEE DOI 1612
BibRef

Littwin, E., Wolf, L.,
Complexity of multiverse networks and their multilayer generalization,
ICPR16(372-377)
IEEE DOI 1705
Complexity theory, Feeds, Joining processes, Neural networks, Nonhomogeneous media, Training, Upper, bound BibRef

Littwin, E., Wolf, L.,
The Multiverse Loss for Robust Transfer Learning,
CVPR16(3957-3966)
IEEE DOI 1612
BibRef

Sharmanska, V., Quadrianto, N.,
Learning from the Mistakes of Others: Matching Errors in Cross-Dataset Learning,
CVPR16(3967-3975)
IEEE DOI 1612
BibRef

Chu, B.[Brian], Madhavan, V.[Vashisht], Beijbom, O.[Oscar], Hoffman, J.[Judy], Darrell, T.J.[Trevor J.],
Best Practices for Fine-Tuning Visual Classifiers to New Domains,
TASKCV16(III: 435-442).
Springer DOI 1611
Fine tuned generic to specific domain. BibRef

Heravi, E.J.[Elnaz Jahani], Aghdam, H.H.[Hamed Habibi], Puig, D.[Domenec],
Training a Mentee Network by Transferring Knowledge from a Mentor Network,
TASKCV16(III: 500-507).
Springer DOI 1611
BibRef

Yan, Y.G.[Yu-Guang], Wu, Q.Y.[Qing-Yao], Tan, M.[Mingkui], Min, H.Q.[Hua-Qing],
Online Heterogeneous Transfer Learning by Weighted Offline and Online Classifiers,
TASKCV16(III: 467-474).
Springer DOI 1611
BibRef

Sun, B., Peng, X.C.[Xing-Chao], Yu, S.X., Saenko, K.,
Ground2sky label transfer for fine-grained aerial car recognition,
ICIP17(360-364)
IEEE DOI 1803
Automobiles, Google, Image color analysis, Image recognition, Image resolution, Object recognition, Task analysis, Label Transfer BibRef

Peng, X.C.[Xing-Chao], Hoffman, J., Yu, S.X., Saenko, K.[Kate],
Fine-to-coarse knowledge transfer for low-res image classification,
ICIP16(3683-3687)
IEEE DOI 1610
Automobiles BibRef

Irie, G.[Go], Arai, H.[Hiroyuki], Taniguchi, Y.[Yukinobu],
Alternating Co-Quantization for Cross-Modal Hashing,
ICCV15(1886-1894)
IEEE DOI 1602
Binary codes BibRef

Shkodrani, S.[Sindi], Hofmann, M.[Michael], Gavves, E.[Efstratios],
Dynamic Adaptation on Non-stationary Visual Domains,
TASKCV18(II:158-171).
Springer DOI 1905
BibRef

Gavves, E., Mensink, T., Tommasi, T., Snoek, C.G.M., Tuytelaars, T.,
Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks,
ICCV15(2731-2739)
IEEE DOI 1602
Computer vision BibRef

Paul, A., Rottensteiner, F., Heipke, C.,
Transfer Learning Based on Logistic Regression,
CMRT15(145-152).
DOI Link 1602
BibRef

Liu, P.C.[Peng-Cheng], Wang, C.[Chong], Yang, P.[Peipei], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu],
Cross-Domain Object Recognition Using Object Alignment,
BMVC15(xx-yy).
DOI Link 1601
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Rochan, M.[Mrigank], Wang, Y.[Yang],
Weakly supervised localization of novel objects using appearance transfer,
CVPR15(4315-4324)
IEEE DOI 1510
BibRef

Dai, D.X.[Deng-Xin], Kroeger, T.[Till], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Metric imitation by manifold transfer for efficient vision applications,
CVPR15(3527-3536)
IEEE DOI 1510
BibRef

Niu, L.[Li], Li, W.[Wen], Xu, D.[Dong],
Visual recognition by learning from web data: A weakly supervised domain generalization approach,
CVPR15(2774-2783)
IEEE DOI 1510
BibRef

Isola, P.[Phillip], Lim, J.J.[Joseph J.], Adelson, E.H.[Edward H.],
Discovering states and transformations in image collections,
CVPR15(1383-1391)
IEEE DOI 1510
BibRef

Royer, A.[Amelie], Lampert, C.H.[Christoph H.],
Classifier adaptation at prediction time,
CVPR15(1401-1409)
IEEE DOI 1510
BibRef

Lu, Y.[Ying], Chen, L.M.[Li-Ming], Saidi, A.[Alexandre], Zhang, Z.X.[Zhao-Xiang], Wang, Y.H.[Yun-Hong],
Learning visual categories through a sparse representation classifier based cross-category knowledge transfer,
ICIP14(165-169)
IEEE DOI 1502
Computer vision BibRef

Kim, J.[Jongdae], Collomosse, J.P.[John P.],
Incremental transfer learning for object recognition in streaming video,
ICIP14(2729-2733)
IEEE DOI 1502
Kernel BibRef

Wang, Z.H.[Zi-Heng], Gao, T.[Tian], Ji, Q.A.[Qi-Ang],
Learning with Hidden Information Using a Max-Margin Latent Variable Model,
ICPR14(1389-1394)
IEEE DOI 1412
Data models BibRef

Zhou, Y.[Yun], Ioannou, I.[Ioanna], Wijewickrema, S.[Sudanthi], Bailey, J.[James], Piromchai, P.[Patorn], Kennedy, G.[Gregor], OLeary, S.[Stephen],
Transfer Learning of a Temporal Bone Performance Model via Anatomical Feature Registration,
ICPR14(1916-1921)
IEEE DOI 1412
Adaptation models BibRef

Fang, Z.[Zheng], Zhang, Z.F.[Zhong-Fei],
Cross Domain Shared Subspace Learning for Unsupervised Transfer Classification,
ICPR14(3927-3932)
IEEE DOI 1412
Accuracy BibRef

Samanta, S.[Suranjana], Selvan, T.[Tirumarai], Das, S.[Sukhendu],
Modeling Sequential Domain Shift through Estimation of Optimal Sub-spaces for Categorization,
BMVC14(xx-yy).
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Farajidavar, N.[Nazli], de Campos, T.[Teofilo], Kittler, J.V.[Josef V.],
Transductive Transfer Machine,
ACCV14(III: 623-639).
Springer DOI 1504
BibRef
And:
Adaptive Transductive Transfer Machine,
BMVC14(xx-yy).
HTML Version. 1410
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Amaral, T.[Telmo], Silva, L.M.[Luís M.], Alexandre, L.A.[Luís A.], Kandaswamy, C.[Chetak], de Sá, J.M.[Joaquim Marques], Santos, J.M.[Jorge M.],
Transfer Learning Using Rotated Image Data to Improve Deep Neural Network Performance,
ICIAR14(I: 290-300).
Springer DOI 1410
BibRef

Branson, S.[Steve], Hjorleifsson, K.E.[Kristjan Eldjarn], Perona, P.[Pietro],
Active Annotation Translation,
CVPR14(3702-3709)
IEEE DOI 1409
active learning. Quickly annotate when previous annotations exist. BibRef

Zhang, B.[Bang], Wang, Y.[Yi], Wang, Y.[Yang], Chen, F.[Fang],
Stable Learning in Coding Space for Multi-class Decoding and Its Extension for Multi-class Hypothesis Transfer Learning,
CVPR14(1075-1081)
IEEE DOI 1409
Multi-class classification; output coding framework; transfer learning BibRef

Tsuchiya, M., Yamauchi, Y., Fujiyoshi, H., Yamashita, T.,
Hybrid Transfer Learning for Efficient Learning in Object Detection,
ACPR13(69-73)
IEEE DOI 1408
feature extraction BibRef

Rana, A.[Aakanksha], Zepeda, J.[Joaquin], Perez, P.[Patrick],
Feature Learning for the Image Retrieval Task,
FSLCV14(III: 152-165).
Springer DOI 1504
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Kulkarni, P.[Praveen], Zepeda, J.[Joaquin], Jurie, F.[Frederic], Pérez, P.[Patrick], Chevallier, L.[Louis],
Learning the Structure of Deep Architectures Using L1 Regularization,
BMVC15(xx-yy).
DOI Link 1601
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Kulkarni, P.[Praveen], Sharma, G.[Gaurav], Zepeda, J.[Joaquin], Chevallier, L.[Louis],
Transfer learning via attributes for improved on-the-fly classification,
WACV14(220-226)
IEEE DOI 1406
Animals BibRef

Long, M.S.[Ming-Sheng], Ding, G.G.[Gui-Guang], Wang, J.M.[Jian-Min], Sun, J.G.[Jia-Guang], Guo, Y.C.[Yu-Chen], Yu, P.S.[Philip S.],
Transfer Sparse Coding for Robust Image Representation,
CVPR13(407-414)
IEEE DOI 1309
image representation; sparse coding; transfer learning BibRef

Kobetski, M.[Miroslav], Sullivan, J.[Josephine],
Discriminative tree-based feature mapping,
BMVC13(xx-yy).
DOI Link 1402
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Kobetski, M.[Miroslav], Sullivan, J.[Josephine],
Apprenticeship Learning: Transfer of Knowledge via Dataset Augmentation,
SCIA13(432-443).
Springer DOI 1311
BibRef

Garcia, E.O.[Esteban O.], de Cote, E.M.[Enrique Munoz], Morales, E.F.[Eduardo F.],
Qualitative Transfer for Reinforcement Learning with Continuous State and Action Spaces,
CIARP13(I:198-205).
Springer DOI 1311
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Chen, S.K.[Shao-Kang], Sanderson, C.[Conrad], Harandi, M.T.[Mehrtash T.], Lovell, B.C.[Brian C.],
Improved Image Set Classification via Joint Sparse Approximated Nearest Subspaces,
CVPR13(452-459)
IEEE DOI 1309
Adaptive Clustering BibRef

Kuzborskij, I.[Ilja], Orabona, F.[Francesco], Caputo, B.[Barbara],
Transfer Learning Through Greedy Subset Selection,
CIAP15(I:3-14).
Springer DOI 1511
BibRef
Earlier:
From N to N+1: Multiclass Transfer Incremental Learning,
CVPR13(3358-3365)
IEEE DOI 1309
LSSVM BibRef

Sharmanska, V.[Viktoriia], Quadrianto, N.[Novi], Lampert, C.H.[Christoph H.],
Learning to Rank Using Privileged Information,
ICCV13(825-832)
IEEE DOI 1403
Learning to rank with more data in training than in test. BibRef

Liu, J.C.[Jing-Chen], McCloskey, S.[Scott], Liu, Y.X.[Yan-Xi],
Training data recycling for multi-level learning,
ICPR12(2314-2318).
WWW Link. 1302
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Shi, Z.Y.[Zhi-Yuan], Siva, P.[Parthipan], Xiang, T.[Tony],
Transfer Learning by Ranking for Weakly Supervised Object Annotation,
BMVC12(78).
DOI Link 1301
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Costa Pereira, J.[Jose], Vasconcelos, N.M.[Nuno M.],
On the regularization of image semantics by modal expansion,
CVPR12(3093-3099).
IEEE DOI 1208
BibRef

Guillaumin, M.[Matthieu], Ferrari, V.[Vittorio],
Large-scale knowledge transfer for object localization in ImageNet,
CVPR12(3202-3209).
IEEE DOI 1208
BibRef

Ye, G.N.[Guang-Nan], Liu, D.[Dong], Jhuo, I.H.[I-Hong], Chang, S.F.[Shih-Fu],
Robust late fusion with rank minimization,
CVPR12(3021-3028).
IEEE DOI 1208
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Aytar, Y.[Yusuf], Zisserman, A.[Andrew],
Tabula rasa: Model transfer for object category detection,
ICCV11(2252-2259).
IEEE DOI 1201
Transfer learning for categories. BibRef

Wang, H.[Hua], Nie, F.P.[Fei-Ping], Huang, H.[Heng], Ding, C.[Chris],
Dyadic transfer learning for cross-domain image classification,
ICCV11(551-556).
IEEE DOI 1201
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Yu, X.D.[Xiao-Dong], Aloimonos, Y.[Yiannis],
Attribute-Based Transfer Learning for Object Categorization with Zero/One Training Example,
ECCV10(V: 127-140).
Springer DOI 1009
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Yao, Y.[Yi], Doretto, G.[Gianfranco],
Boosting for transfer learning with multiple sources,
CVPR10(1855-1862).
IEEE DOI 1006
Transfer info between domains. BibRef

Lampert, C.H.[Christoph H.], Krömer, O.[Oliver],
Weakly-Paired Maximum Covariance Analysis for Multimodal Dimensionality Reduction and Transfer Learning,
ECCV10(II: 566-579).
Springer DOI 1009
BibRef

Ahmed, A.[Amr], Yu, K.[Kai], Xu, W.[Wei], Gong, Y.H.[Yi-Hong], Xing, E.[Eric],
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks,
ECCV08(III: 69-82).
Springer DOI 0810
BibRef

Quattoni, A.[Ariadna], Collins, M.[Michael], Darrell, T.J.[Trevor J.],
Transfer learning for image classification with sparse prototype representations,
CVPR08(1-8).
IEEE DOI 0806
BibRef
And: CSAIL-2008-012, March 2008.
WWW Link. BibRef
Earlier:
Learning Visual Representations using Images with Captions,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Domain Adaptation .