[1] [1] WU H, YOKOYAMA T, PRAMADIHANTO D, et al. Face and facial feature extraction from color image [C]//Proceedings of the Second International Conference on Automatic Face and Gesture Recognition. Killington, VT, USA: IEEE, 1996: 345-350.

[2] [2] SHI Y X, REN X X, YANG S Z, et al. A generalized Kernel Fisher Discriminant framework used for feature extraction and face recognition [C]//Proceedings of the 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). Changsha, China: IEEE, 2016: 1487-1491.

[3] [3] LU Z, JIANG X D, KOT A. Deep coupled ResNet for low-resolution face recognition [J]. IEEE Signal Processing Letters, 2018, 25(4): 526-530.

[4] [4] SCHMID C, MOHR R. Local grayvalue invariants for image retrieval [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(5): 530-535.

[5] [5] RAZA A, DAWOOD H, DAWOOD H, et al. Correlated primary visual Texton histogram features for content base image retrieval [J]. IEEE Access, 2018, 6: 46595-46616.

[6] [6] XIANG J, ZHANG N, PAN R R, et al. Fabric image retrieval system using hierarchical search based on deep convolutional neural network [J]. IEEE Access, 2019, 7: 35405-35417.

[7] [7] PHAM T T D, KIM S, LU Y C, et al. Facial action units-based image retrieval for facial expression recognition [J]. IEEE Access, 2019, 7: 5200-5207.

[8] [8] DONG Z, JING C C, PEI M T, et al. Deep CNN based binary hash video representations for face retrieval [J]. Pattern Recognition, 2018, 81: 357-369.

[9] [9] NAGPAL S, SINGH M, SINGH R, et al. Regularized deep learning for face recognition with weight variations [J]. IEEE Access, 2015, 3: 3010-3018.

[10] [10] ABUZNEID M A, MAHMOOD A. Enhanced human face recognition using LBPH descriptor, Multi-KNN, and back-propagation neural network [J]. IEEE Access, 2018, 6: 20641-20651.

[15] [15] SUN Y, CHEN Y H, WANG X G, et al. Deep learning face representation by joint identification-verification [C]//Proceedings of the 27th International Conference on Neural Information Processing Systems. Montreal, Canada: MIT Press, 2014: 1988-1996.

[16] [16] ZHANG M M, LI W, DU Q. Diverse region-based CNN for hyperspectral image classification [J]. IEEE Transactions on Image Processing, 2018, 27(6): 2623-2634.

[17] [17] ZHAO Y D, HAO K R, HE H B, et al. A visual long-short-term memory based integrated CNN model for fabric defect image classification [J]. Neurocomputing, 2020, 380: 259-270.

[18] [18] SARDOGAN M, TUNCER A, OZEN Y. Plant leaf disease detection and classification based on CNN with LVQ algorithm [C]//2018 3rd International Conference on Computer Science and Engineering (UBMK). Sarajevo, Bosnia-Herzegovina: IEEE, 2018: 382-385.

[19] [19] GE W F, HUANG W L, DONG D K, et al. Deep metric learning with hierarchical triplet loss [C]//Proceedings of the European Conference on Computer Vision (ECCV). Munich, Germany: Springer, 2018: 272-288.

[20] [20] CHEN W H, CHEN X T, ZHANG J G, et al. Beyond triplet loss: A deep quadruplet network for person re-identification [C]//Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Honolulu, HI, USA: IEEE, 2017: 1320-1329.

[21] [21] LV X B, ZHAO C R, CHEN W. A novel hard mining center-triplet loss for person re-identification [C]//Chinese Conference on Pattern Recognition and Computer Vision (PRCV). Xi′an, China: Springer, 2019: 199-210.

[22] [22] YAO H P, FU D Y, ZHANG P Y, et al. MSML: A novel multilevel semi-supervised machine learning framework for intrusion detection system [J]. IEEE Internet of Things Journal, 2019, 6(2): 1949-1959.

[23] [23] SUN Y, LIANG D, WANG X G, et al. DeepID3: Face recognition with very deep neural networks [J]. arXiv preprint arXiv: 1502.00873, 2015.

[24] [24] LIN T Y, GOYAL P, GIRSHICK R, et al. Focal loss for dense object detection [C]//Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV). Venice, Italy: IEEE, 2017: 2999-3007.

[25] [25] WANG C, LAN X P, ZHANG X. How to train triplet networks with 100 K identities? [C]//Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). Venice, Italy: IEEE, 2017: 1907-1915.

[26] [26] ZHANG H J, JI Y Z, HUANG W, et al. Sitcom-star-based clothing retrieval for video advertising: a deep learning framework [J]. Neural Computing and Applications, 2019, 31: 7361-7380.