22.2.9.4 Learning Face Detection, Neural Nets, SVM

Zhong, Y., Chen, J., Huang, B.,
Toward End-to-End Face Recognition Through Alignment Learning,
SPLetters(24), No. 8, August 2017, pp. 1213-1217.
IEEE DOI 1708
face recognition, learning (artificial intelligence), LFW dataset, alignment learning, automatic learning, end-to-end face recognition, face recognition methods, geometric transformations, human face structure, recognition feature extraction, Convolution, Face, Face detection, Face recognition, Feature extraction, Training, End-to-end (e2e) training, face alignment, face recognition, spatial, transformer BibRef

Li, H., Hu, H., Yip, C.,
Comments on 'Iterative Re-Constrained Group Sparse Face Recognition With Adaptive Weights Learning',
IP(26), No. 11, November 2017, pp. 5475-5476.
IEEE DOI 1709
Adaptation models, Convergence, Face recognition, Image reconstruction, Lagrangian functions, Probes, Xenon
See also Iterative Re-Constrained Group Sparse Face Recognition With Adaptive Weights Learning. BibRef

Lin, L.[Liang], Wang, K.[Keze], Meng, D.Y.[De-Yu], Zuo, W.M.[Wang-Meng], Zhang, L.[Lei],
Active Self-Paced Learning for Cost-Effective and Progressive Face Identification,
PAMI(40), No. 1, January 2018, pp. 7-19.
IEEE DOI 1712
Face, Face recognition, Feature extraction, Neural networks, Noise measurement, Optimization, Training, Cost-effective model, self-paced learning
See also Joint Learning of Multiple Regressors for Single Image Super-Resolution. BibRef

Wang, F.Q.[Fa-Qiang], Zuo, W.M.[Wang-Meng], Lin, L.[Liang], Zhang, D.[David], Zhang, L.[Lei],
Joint Learning of Single-Image and Cross-Image Representations for Person Re-identification,
CVPR16(1288-1296)
IEEE DOI 1612
BibRef

Cao, G.Q.[Guan-Qun], Iosifidis, A.[Alexandros], Gabbouj, M.[Moncef],
Neural class-specific regression for face verification,
IET-Bio(7), No. 1, January 2018, pp. 63-70.
DOI Link 1712
BibRef

Tran, D.T., Kiranyaz, S., Gabbouj, M., Iosifidis, A.,
Knowledge Transfer for Face Verification Using Heterogeneous Generalized Operational Perceptrons,
ICIP19(1168-1172)
IEEE DOI 1910
Face Verification, Generalized Operational Perceptron, Progressive Neural Network Learning BibRef

Zheng, L.[Lilei], Duffner, S., Idrissi, K., Garcia, C., Baskurt, A.,
Pairwise Identity Verification via Linear Concentrative Metric Learning,
Cyber(48), No. 1, January 2018, pp. 324-335.
IEEE DOI 1801
BibRef
Earlier: A1, A3, A4, A2, A5:
Triangular similarity metric learning for face verification,
FG15(1-7)
IEEE DOI 1508
Cost function, Data models, Face, Learning systems, Measurement, Training, Training data, Face verification, identity verification, speaker verification BibRef

Ranjan, R., Sankaranarayanan, S., Bansal, A., Bodla, N., Chen, J.C., Patel, V.M., Castillo, C.D., Chellappa, R.,
Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans,
SPMag(35), No. 1, January 2018, pp. 66-83.
IEEE DOI 1801
Biometrics, Detectors, Face recognition, Feature extraction, Graphics processing, Machine learning, Neural networks, Videos BibRef

Lu, Z.[Ze], Jiang, X.D.[Xu-Dong], Kot, A.C.[Alex C.],
Color space construction by optimizing luminance and chrominance components for face recognition,
PR(83), 2018, pp. 456-468.
Elsevier DOI 1808
BibRef
Earlier:
Enhance deep learning performance in face recognition,
ICIVC17(244-248)
IEEE DOI 1708
Color face recognition, Color space, Color sensor analysis, Chrominance subspace, Discriminant analysis, Covariance analysis. Databases, Face, Face recognition, Feature extraction, Image representation, Principal component analysis, Training, CNNs, VGG-face, fine-tuning, raw pixels BibRef

Banerjee, S., Das, S.,
LR-GAN for degraded Face Recognition,
PRL(116), 2018, pp. 246-253.
Elsevier DOI 1812
BibRef
Earlier:
Soft-Margin Learning for Multiple Feature-Kernel Combinations with Domain Adaptation, for Recognition in Surveillance Face Datasets,
Biometrics16(237-242)
IEEE DOI 1612
GAN, Face Recognition, DA, Nash equilibrium, PMSE, Jensen-Shannon divergence BibRef

Yu, B., Tao, D.,
Anchor Cascade for Efficient Face Detection,
IP(28), No. 5, May 2019, pp. 2490-2501.
IEEE DOI 1903
convolutional neural nets, face recognition, image classification, learning (artificial intelligence), cascade face detection BibRef

Villamizar, M.[Michael], Sanfeliu, A.[Alberto], Moreno-Noguer, F.[Francesc],
Online learning and detection of faces with low human supervision,
VC(35), No. 3, March 2019, pp. 349-370.
WWW Link. 1906
BibRef

Wu, W.Q.[Wen-Qi], Yin, Y.J.[Ying-Jie], Wang, X.G.[Xin-Gang], Xu, D.[De],
Face Detection With Different Scales Based on Faster R-CNN,
Cyber(49), No. 11, November 2019, pp. 4017-4028.
IEEE DOI 1908
convolutional neural nets, face recognition, feature extraction, learning (artificial intelligence), Faster R-CNN BibRef

Kefi-Fatteh, T.[Takoua], Ksantini, R.[Riadh], Kaâniche, M.B.[Mohamed-Bécha], Bouhoula, A.[Adel],
Human Face Detection Improvement Using Incremental Learning Based on Low Variance Directions,
SIViP(13), No. 8, November 2019, pp. 1503-1510.
Springer DOI 1911
BibRef
Earlier: ACIVS17(170-179).
Springer DOI 1712
BibRef

Massoli, F.V.[Fabio Valerio], Amato, G.[Giuseppe], Falchi, F.[Fabrizio],
Cross-resolution learning for Face Recognition,
IVC(99), 2020, pp. 103927.
Elsevier DOI 2006
Deep learning, Low resolution Face Recognition, Cross resolution Face Recognition BibRef

Zhou, Z.X.[Ze-Xun], He, Z.S.[Zhong-Shi], Jia, Y.Y.[Yuan-Yuan], Du, J.L.[Jing-Long], Wang, L.[Lulu], Chen, Z.Y.[Zi-Yu],
Context prior-based with residual learning for face detection: A deep convolutional encoder-decoder network,
SP:IC(88), 2020, pp. 115948.
Elsevier DOI 2009
Context prior, Residual learning, Deep convolutional neural network, Encoder-decoder, Face detection BibRef

Huang, Y.[Yuge], Shen, P.C.[Peng-Cheng], Tai, Y.[Ying], Li, S.X.[Shao-Xin], Liu, X.M.[Xiao-Ming], Li, J.L.[Ji-Lin], Huang, F.Y.[Fei-Yue], Ji, R.R.[Rong-Rong],
Improving Face Recognition from Hard Samples via Distribution Distillation Loss,
ECCV20(XXX: 138-154).
Springer DOI 2010
BibRef

Huang, Y.H.[Yu-Hsuan], Chen, H.H.[Homer H.],
Deep face recognition for dim images,
PR(126), 2022, pp. 108580.
Elsevier DOI 2204
BibRef
Earlier:
Face Recognition Under Low Illumination Via Deep Feature Reconstruction Network,
ICIP20(2161-2165)
IEEE DOI 2011
Face recognition, Dim image, Rank-1 identification accuracy, Two-branch network, Convolutional neural network. illumination-invariant, illumination-robust, reconstruction network, illumination pre-processing. BibRef

Zhang, S.F.[Shi-Feng], Chi, C.[Cheng], Lei, Z.[Zhen], Li, S.Z.[Stan Z.],
RefineFace: Refinement Neural Network for High Performance Face Detection,
PAMI(43), No. 11, November 2021, pp. 4008-4020.
IEEE DOI 2110
Face, Detectors, Face detection, Feature extraction, Task analysis, Proposals, Neural networks, Face detection, refinement network, high performance BibRef

Yang, X.B.[Xian-Ben], Zhang, W.[Wei],
Heterogeneous face detection based on multi-task cascaded convolutional neural network,
IET-IPR(16), No. 1, 2022, pp. 207-215.
DOI Link 2112
BibRef

Chen, B.J.[Bei-Jing], Liu, X.[Xin], Zheng, Y.H.[Yu-Hui], Zhao, G.Y.[Guo-Ying], Shi, Y.Q.[Yun-Qing],
A Robust GAN-Generated Face Detection Method Based on Dual-Color Spaces and an Improved Xception,
CirSysVideo(32), No. 6, June 2022, pp. 3527-3538.
IEEE DOI 2206
Faces, Feature extraction, Image color analysis, Convolution, Face detection, Robustness, Convolutional neural networks, color space BibRef

Zhou, J.C.[Jian-Can], Jia, X.[Xi], Li, Q.[Qiufu], Shen, L.L.[Lin-Lin], Duan, J.M.[Jin-Ming],
UniFace: Unified Cross-Entropy Loss for Deep Face Recognition,
ICCV23(20673-20682)
IEEE DOI 2401
BibRef

Himmi, S.[Saad], Parret, V.[Vincent], Chhatkuli, A.[Ajad], Van Gool, L.J.[Luc J.],
MS-EVS: Multispectral event-based vision for deep learning based face detection,
WACV24(605-614)
IEEE DOI 2404
Image color analysis, Multispectral imaging, Prototypes, Gray-scale, Sensors, High dynamic range, Face detection, Algorithms, Embedded sensing / real-time techniques BibRef

Jiang, C.C.[Chen-Chen], Ma, H.B.[Hong-Bing], Li, L.L.[Liang-Liang],
IRNet: An Improved RetinaNet Model for Face Detection,
ICIVC22(129-134)
IEEE DOI 2301
Training, Manuals, Feature extraction, Real-time systems, Hardware, Face detection, Faces, face detection, RetinaNet, feature fusion, weight decay BibRef

Liu, Y.[Yang], Wang, F.[Fei], Deng, J.K.[Jian-Kang], Zhou, Z.P.[Zhi-Peng], Sun, B.[Baigui], Li, H.[Hao],
MogFace: Towards a Deeper Appreciation on Face Detection,
CVPR22(4083-4092)
IEEE DOI 2210
Codes, Face recognition, Detectors, Object detection, Feature extraction, Face detection, Data mining, Face and gestures, retrieval BibRef

Liu, S.L.[Shi-Long], Zhang, L.[Lei], Yang, X.[Xiao], Su, H.[Hang], Zhu, J.[Jun],
Unsupervised Part Segmentation through Disentangling Appearance and Shape,
CVPR21(8351-8360)
IEEE DOI 2111
Geometry, Shape, Annotations, Face recognition, Semantics, Neural networks BibRef

Xiao, Z.H.[Zi-Hao], Gao, X.F.[Xian-Feng], Fu, C.L.[Chi-Lin], Dong, Y.P.[Yin-Peng], Gao, W.[Wei], Zhang, X.L.[Xiao-Lu], Zhou, J.[Jun], Zhu, J.[Jun],
Improving Transferability of Adversarial Patches on Face Recognition with Generative Models,
CVPR21(11840-11849)
IEEE DOI 2111
Manifolds, Face recognition, Perturbation methods, Authentication, Robustness, Security BibRef

Yang, X.[Xiao], Wei, F.Y.[Fang-Yun], Zhang, H.Y.[Hong-Yang], Zhu, J.[Jun],
Design and Interpretation of Universal Adversarial Patches in Face Detection,
ECCV20(XVII:174-191).
Springer DOI 2011
BibRef

Ghosh, S.S., Hua, Y., Mukherjee, S.S., Robertson, N.M.,
Improving Detection And Recognition Of Degraded Faces By Discriminative Feature Restoration Using GAN,
ICIP20(2146-2150)
IEEE DOI 2011
Face recognition, Faces, Facial features, Image recognition, Image restoration, CNN, GAN, detection, recognition, degraded face image BibRef

Zhu, J.S.[Jia-Shu], Li, D.[Dong], Han, T.T.[Tian-Tian], Tian, L.[Lu], Shan, Y.[Yi],
Progressface: Scale-aware Progressive Learning for Face Detection,
ECCV20(VI:344-360).
Springer DOI 2011
BibRef

Sanchez Tapia, L., Pattichis, M.S., Celedón-Pattichis, S., López Leiva, C.,
The Importance of the Instantaneous Phase for Face Detection using Simple Convolutional Neural Networks,
SSIAI20(1-4)
IEEE DOI 2009
channel bank filters, convolutional neural nets, face recognition, image filtering, image representation, low-complexity neural networks BibRef

Huang, Y., Wang, Y., Tai, Y., Liu, X., Shen, P., Li, S., Li, J., Huang, F.,
CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition,
CVPR20(5900-5909)
IEEE DOI 2008
Training, Face recognition, Modulation, Convergence, Face, Adaptation models, Tuning BibRef

Winter, M.[Martin], Bailer, W.[Werner],
Incremental Training for Face Recognition,
MMMod19(I:289-299).
Springer DOI 1901
BibRef

Lezama, J., Qiu, Q., Musé, P., Sapiro, G.,
OLE: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning,
CVPR18(8109-8118)
IEEE DOI 1812
Training, Standards, Neural networks, Face, Measurement, Optimization BibRef

Kortylewski, A., Egger, B., Schneider, A., Gerig, T., Morel-Forster, A., Vetter, T.,
Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems,
AMFG18(2174-217409)
IEEE DOI 1812
Face, Face recognition, Lighting, Generators, Training data, Computer architecture, Task analysis BibRef

Siddiqui, S., Vatsa, M., Singh, R.,
Face Recognition for Newborns, Toddlers, and Pre-School Children: A Deep Learning Approach,
ICPR18(3156-3161)
IEEE DOI 1812
Pediatrics, Databases, Face, Face recognition, Feature extraction, Principal component analysis, Iris recognition BibRef

Jamal, M.A., Li, H., Gong, B.,
Deep Face Detector Adaptation Without Negative Transfer or Catastrophic Forgetting,
CVPR18(5608-5618)
IEEE DOI 1812
Detectors, Face, Training, Adaptation models, Cost function, Face detection BibRef

Song, G., Liu, Y., Jiang, M., Wang, Y., Yan, J., Leng, B.,
Beyond Trade-Off: Accelerate FCN-Based Face Detector with Higher Accuracy,
CVPR18(7756-7764)
IEEE DOI 1812
Face, Face detection, Proposals, Acceleration, Detectors, Estimation, Feature extraction BibRef

Le, C., Ma, H., Wang, X., Li, X.,
Key Parts Context and Scene Geometry in Human Head Detection,
ICIP18(1897-1901)
IEEE DOI 1809
Head, Detectors, Geometry, Task analysis, Training, Shape, Head detection, key parts context, scene geometry, convolutional neural network BibRef

Sun, Z., Peng, D., Cai, Z., Chen, Z., Jin, L.,
Scale Mapping and Dynamic Re-Detecting in Dense Head Detection,
ICIP18(1902-1906)
IEEE DOI 1809
Head, Proposals, Training, Task analysis, Testing, Object detection, Complexity theory, Object detection, convolutional neural network BibRef

Shi, W., Pattichis, M.S., Celedón-Pattichis, S., López Leiva, C.,
Robust Head Detection in Collaborative Learning Environments Using AM-FM Representations,
Southwest18(1-4)
IEEE DOI 1809
Hair, Frequency modulation, Face, Detectors, Robustness, Image color analysis, head detection, face detection, AM-FM representations BibRef

Chen, J., Lin, W., Zheng, J., Chellappa, R.,
A Real-Time Multi-Task Single Shot Face Detector,
ICIP18(176-180)
IEEE DOI 1809
Face, Task analysis, Detectors, Pose estimation, Face detection, face detection, fiducial detection, head pose estimation BibRef

Filali, H., Riffi, J., Mahraz, A.M., Tairi, H.,
Multiple face detection based on machine learning,
ISCV18(1-8)
IEEE DOI 1807
Gabor filters, face recognition, feature extraction, image classification, learning (artificial intelligence), Machine Learning BibRef

Nguyen-Meidine, L.T., Granger, E., Kiran, M., Blais-Morin, L.A.,
A comparison of CNN-based face and head detectors for real-time video surveillance applications,
IPTA17(1-7)
IEEE DOI 1804
computational complexity, face recognition, feedforward neural nets, image resolution, object detection, Video Surveillance BibRef

Zhang, H., Liu, H., Guo, D., Sun, F.,
From foot to head: Active face finding using deep Q-learning,
ICIP17(1862-1866)
IEEE DOI 1803
Cameras, Face, Learning (artificial intelligence), Manipulators, Testing, Training, Active face finding, Deep Q-learning BibRef

Zhang, G., Tu, E., Cui, D.,
Stable and improved generative adversarial nets (GANS): A constructive survey,
ICIP17(1871-1875)
IEEE DOI 1803
Convolution, Face, Generators, Pipelines, Task analysis, Training, GAN, generative adversarial networks, stable GAN BibRef

Hsu, G.S., Hsieh, C.H.,
Multi-dropout regression for wide-angle landmark localization,
ICIP17(3830-3834)
IEEE DOI 1803
Convolution, Databases, Detectors, Face, Face detection, Feature extraction, Training, Convolutional Neural Network, Face Alignment BibRef

Hu, G.S.[Guo-Sheng], Hua, Y.[Yang], Yuan, Y., Zhang, Z., Lu, Z., Mukherjee, S.S., Hospedales, T.M., Robertson, N.M.[Neil M.], Yang, Y.,
Attribute-Enhanced Face Recognition with Neural Tensor Fusion Networks,
ICCV17(3764-3773)
IEEE DOI 1802
face recognition, feature extraction, image fusion, learning (artificial intelligence), neural nets, optimisation, Tensile stress BibRef

Zhang, K., Zhang, Z., Wang, H., Li, Z., Qiao, Y., Liu, W.,
Detecting Faces Using Inside Cascaded Contextual CNN,
ICCV17(3190-3198)
IEEE DOI 1802
convolution, face recognition, image classification, image enhancement, learning (artificial intelligence), Training BibRef

Wang, J., Wang, B., Zheng, Y., Liu, W.,
Research and Implementation on Face Detection Approach Based on Cascaded Convolutional Neural Networks,
ICVISP17(34-39)
IEEE DOI 1712
Erbium, Signal processing, deep learning, face detection, multi-task learning BibRef

Khadhraoui, T.[Taher], Amiri, H.[Hamid],
Face Recognition with Single Training Sample per Subject,
CIAP17(II:202-212).
Springer DOI 1711
BibRef

Deng, J.K.[Jian-Kang], Zhou, Y.X.[Yu-Xiang], Zafeiriou, S.P.[Stefanos P.],
Marginal Loss for Deep Face Recognition,
FaceWild17(2006-2014)
IEEE DOI 1709
Databases, Face, Face recognition, Robustness, Standards, Training, Training, data BibRef

Mao, M.[Minqi], Zheng, Z.L.[Zhong-Long], Chen, Z.Y.[Zhong-Yu], Liu, H.W.[Hua-Wen], He, X.W.[Xiao-Wei], Ye, R.H.[Rong-Hua],
Group and collaborative dictionary pair learning for face recognition,
ICPR16(4107-4111)
IEEE DOI 1705
Algorithm design and analysis, Collaboration, Databases, Dictionaries, Encoding, Face recognition, Training, Collaborative, Dictionary Pair Learning, Face Recognition, Group BibRef

Yang, Z.[Zhenheng], Nevatia, R.,
A multi-scale cascade fully convolutional network face detector,
ICPR16(633-638)
IEEE DOI 1705
Detectors, Face, Face detection, Heating systems, Proposals, Streaming media, Training BibRef

Chariton, A.[Alexandros], Passalis, N.[Nikolaos], Tefas, A.[Anastasios],
Bag-Of-Features-Based Knowledge Distillation For Lightweight Convolutional Neural Networks,
ICIP22(1541-1545)
IEEE DOI 2211
Knowledge engineering, Convolution, Neural networks, Pipelines, Network architecture, Feature extraction, Convolutional Neural Networks BibRef

Passalis, N.[Nikolaos], Tefas, A.[Anastasios],
Learning Deep Representations with Probabilistic Knowledge Transfer,
ECCV18(XI: 283-299).
Springer DOI 1810
BibRef
Earlier:
Learning Discriminative Representations for Big Data Clustering Using Similarity-Based Dimensionality Reduction,
IVMSP18(1-5)
IEEE DOI 1809
BibRef
Earlier:
Learning Bag-of-Features Pooling for Deep Convolutional Neural Networks,
ICCV17(5766-5774)
IEEE DOI 1802
Task analysis, Optimization, Clustering algorithms, Dimensionality reduction, Robustness, Clustering methods, Linear programming. convolution, feature extraction, image classification, image representation, Training BibRef

Tzelepi, M., Tefas, A.,
Fully Unsupervised Optimization of CNN Features Towards Content Based Image Retrieval,
IVMSP18(1-5)
IEEE DOI 1809
Task analysis, Image retrieval, Feature extraction, Adaptation models, Image representation, Computer architecture, Deep Learning BibRef

Triantafyllidou, D., Tefas, A.,
Face detection based on deep convolutional neural networks exploiting incremental facial part learning,
ICPR16(3560-3565)
IEEE DOI 1705
Computational modeling, Convolution, Detectors, Face, Face detection, Neural networks, Training BibRef

Guan, Y., Lu, T., Zhang, Y., Wang, B., Li, X., Xiong, Z.,
Efficient low-rank supported extreme learning machine for robust face recognition,
VCIP16(1-4)
IEEE DOI 1701
Algorithm design and analysis BibRef

Wang, K., Dong, Y., Bai, H., Zhao, Y., Hu, K.,
Use fast R-CNN and cascade structure for face detection,
VCIP16(1-4)
IEEE DOI 1701
Calibration BibRef

Vizilter, Y., Gorbatsevich, V., Vorotnikov, A., Kostromov, N.,
Real-Time Face Identification via CNN and Boosted Hashing Forest,
Biometrics16(146-154)
IEEE DOI 1612
BibRef

Ghazi, M.M., Ekenel, H.K.,
A Comprehensive Analysis of Deep Learning Based Representation for Face Recognition,
Biometrics16(102-109)
IEEE DOI 1612
BibRef

Qin, H.W.[Hong-Wei], Yan, J.J.[Jun-Jie], Li, X.[Xiu], Hu, X.L.[Xiao-Lin],
Joint Training of Cascaded CNN for Face Detection,
CVPR16(3456-3465)
IEEE DOI 1612
BibRef

Li, Y.Z.[Yun-Zhu], Sun, B.Y.[Ben-Yuan], Wu, T.F.[Tian-Fu], Wang, Y.Z.[Yi-Zhou],
Face Detection with End-to-End Integration of a ConvNet and a 3D Model,
ECCV16(III: 420-436).
Springer DOI 1611
BibRef

Lin, S., Su, F.,
FCFD: Teach the machine to accomplish face detection step by step,
ICIP16(3214-3218)
IEEE DOI 1610
Detectors BibRef

Chowdhury, A.R., Lin, T.Y., Maji, S., Learned-Miller, E.G.[Erik G.],
One-to-many face recognition with bilinear CNNs,
WACV16(1-9)
IEEE DOI 1606
Benchmark testing BibRef

Iosifidis, A.[Alexandros], Tefas, A.[Anastasios], Pitas, I.[Ioannis],
Large-scale nonlinear facial image classification based on approximate kernel Extreme Learning Machine,
ICIP15(2449-2453)
IEEE DOI 1512
Approximate Methods BibRef

Li, H.X.[Hao-Xiang], Lin, Z.[Zhe], Shen, X.H.[Xiao-Hui], Brandt, J.[Jonathan], Hua, G.[Gang],
A convolutional neural network cascade for face detection,
CVPR15(5325-5334)
IEEE DOI 1510
BibRef

Shao, M.[Ming], Ding, Z.M.[Zheng-Ming], Fu, Y.[Yun],
Sparse low-rank fusion based deep features for missing modality face recognition,
FG15(1-6)
IEEE DOI 1508
face recognition Not all modalities in learning. BibRef

Thakur, S., Sing, J.K., Basu, D.K., Nasipuri, M.,
Face Recognition Using Posterior Distance Model Based Radial Basis Function Neural Networks,
PReMI09(470-475).
Springer DOI 0912
BibRef

Zhuang, S.S.[Shin-Shan], Lai, S.H.[Shang-Hong],
Face detection directly from h.264 compressed video with convolutional neural network,
ICIP09(2485-2488).
IEEE DOI 0911
BibRef

Zhang, Y.[Yan], Zhang, T.[Tao],
Combining Variation in the Bayesian Face Recognition,
CISP09(1-4).
IEEE DOI 0910
BibRef

Onis, S., Sanson, H., Garcia, C.,
Iterative unsupervised object detection system,
WSSIP08(397-400).
IEEE DOI 0806
Apply to faces. Give a few expamples, learn. BibRef

Tian, C.[Chunna], Fan, G.L.[Guo-Liang], Gao, X.B.[Xin-Bo],
Multi-view face recognition by nonlinear tensor decomposition,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Tian, C.[Chunna], Gao, X.B.[Xin-Bo], Li, J.[Jie],
A Valid Multi-View Face Detection Tree Based on Floatboost Learning,
ICIP06(2653-2656).
IEEE DOI 0610
BibRef

Bredin, H.[Herve], Dehak, N.[Najim], Chollet, G.[Gerard],
GMM-based SVM for face recognition,
ICPR06(III: 1111-1114).
IEEE DOI 0609
BibRef

He, X.G.[Xiao-Guang], Tian, J.[Jie], He, Y.L.[Yu-Liang], Yang, X.[Xin],
Face Recognition with Relative Difference Space and SVM,
ICPR06(III: 527-531).
IEEE DOI 0609
BibRef

Abeni, P., Baltatu, M.[Madalina], d'Alessandro, R.[Rosalia],
User Authentication based on Face Recognition with Support Vector Machines,
CRV06(42-42).
IEEE DOI 0607
BibRef

Gates, K.E.,
Fast and Accurate Face Recognition Using Support Vector Machines,
FRGC05(III: 163-163).
IEEE DOI 0507
BibRef

Jin, H.L.[Hong-Liang], Liu, Q.S.[Qing-Shan], Lu, H.Q.[Han-Qing],
Face detection using one-class-based support vectors,
AFGR04(457-462).
IEEE DOI 0411
BibRef

Chen, J.[Jie], Chen, X.L.[Xi-Lin], Gao, W.[Wen],
Expand training set for face detection by GA re-sampling,
AFGR04(73-78).
IEEE DOI 0411
BibRef
And:
Resampling for face detection by self-adaptive genetic algorithm,
ICPR04(III: 822-825).
IEEE DOI 0409
BibRef

Fang, J., Qiu, G.,
Face Detection Based on Multiple Regression and Recognition Support Vector Machines,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Penev, P.S.[Penio S.],
Learning a Synchronous MAP for Improved Face Recognition,
LCV04(106).
IEEE DOI 0406
BibRef

Wu, Y.M.[Yi-Ming], Chan, K.L.[Kap Luk], Wang, L.[Lei],
Face recognition based on discriminative manifold learning,
ICPR04(IV: 171-174).
IEEE DOI 0409
BibRef

Cui, G.Q.[Guo-Qin], Gao, W.[Wen],
Support vector machines for face recognition with two-layer generated virtual data,
ICPR04(III: 570-573).
IEEE DOI 0409
BibRef

Sun, J.[Jie], Rehg, J.M., Bobick, A.F.,
Automatic cascade training with perturbation bias,
CVPR04(II: 276-283).
IEEE DOI 0408
Cascade learning for face detection. BibRef

Fransens, R., DePrins, J., Van Gool, L.J.,
SVM-based nonparametric discriminant analysis, an application to face detection,
ICCV03(1289-1296).
IEEE DOI 0311
BibRef

Zhang, B.L.[Bai-Ling], Guo, Y.[Yan],
Face Recognition by Auto-associative Radial Basis Function Network,
AVBPA01(52).
Springer DOI 0310
BibRef

Ma, Y.[Yong], Ding, X.Q.[Xiao-Qing],
Face detection based on hierarchical support vector machines,
ICPR02(I: 222-225).
IEEE DOI 0211
BibRef

Ma, Y.[Yong], Ding, X.Q.[Xiao-Qing],
Real-time rotation invariant face detection based on cost-sensitive AdaBoost,
ICIP03(III: 921-924).
IEEE DOI 0312
BibRef

Kim, T.K.[Tae-Kyun], Kong, D.G.[Dong-Geon], Kim, S.R.[Sang-Ryong],
Learning a decision boundary for face detection,
ICIP02(I: 920-923).
IEEE DOI 0210
BibRef

Sahbi, H., Boujemaa, N.,
Coarse-to-fine support vector classifiers for face detection,
ICPR02(III: 359-362).
IEEE DOI 0211
BibRef

Sahbi, H., Boujemaa, N.,
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Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Face Detection in Video .

Last update:Aug 28, 2024 at 16:02:19