基于改进AlexNet的人脸表情识别 下载: 1512次
杨旭, 尚振宏. 基于改进AlexNet的人脸表情识别[J]. 激光与光电子学进展, 2020, 57(14): 141026.
Xu Yang, Zhenhong Shang. Facial Expression Recognition Based on Improved AlexNet[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141026.
[1] Mehrabian A, Epstein N. A measure of emotional empathy[J]. Journal of Personality, 1972, 40(4): 525-543.
[2] Cootes T F, Taylor C J, Cooper D H, et al. Active shape models-their training and application[J]. Computer Vision and Image Understanding, 1995, 61(1): 38-59.
[3] LyonsM, AkamatsuS, KamachiM, et al. Coding facial expressions withGabor wavelets[C]∥Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition, April 14-16, 1998, Nara, Japan. New York: IEEE, 1998: 200- 205.
[4] Ojala T, Pietikainen M, Maenpaa T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(7): 971-987.
[5] 卢官明, 何嘉利, 闫静杰, 等. 一种用于人脸表情识别的卷积神经网络[J]. 南京邮电大学学报(自然科学版), 2016, 36(1): 16-22.
Lu G M, He J L, Yan J J, et al. Convolutional neural network for facial expression recognition[J]. Journal of Nanjing University of Posts and Telecommunications (Natural Science Edition), 2016, 36(1): 16-22.
[6] ZhouS, Liang YY, WanJ, et al.Facial expression recognition based on multi-scale CNNS[M] ∥Biometric Recognition. Cham: Springer International Publishing, 2016: 503- 510.
[7] XuM, ChengW, ZhaoQ, et al. Facial expression recognition based on transfer learning from deep convolutional networks[C]∥2015 11th International Conference on Natural Computation (ICNC), August 15-17, 2015, Zhangjiajie, China. New York: IEEE, 2015: 702- 708.
[8] 曹金梦, 倪蓉蓉, 杨彪. 面向面部表情识别的双通道卷积神经网络[J]. 南京师范大学学报(工程技术版), 2018, 18(3): 1-9.
Cao J M, Ni R R, Yang B. Binary-channel convolutional neural network for facial expression recognition[J]. Journal of Nanjing Normal University (Engineering and Technology Edition), 2018, 18(3): 1-9.
[9] CaiJ, Meng ZB, Khan AS, et al. Island loss for learning discriminative features in facial expression recognition[C]∥2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), May 15-19, 2018, Xi'an, China. New York: IEEE, 2018: 302- 309.
[10] 吴慧华, 苏寒松, 刘高华, 等. 基于余弦距离损失函数的人脸表情识别算法[J]. 激光与光电子学进展, 2019, 56(24): 241502.
[11] 王琳琳, 刘敬浩, 付晓梅. 融合局部特征与深度置信网络的人脸表情识别[J]. 激光与光电子学进展, 2018, 55(1): 011002.
[12] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Advances in Neural Information Processing Systems, 2012, 25(2): 1097-1105.
[13] LinM, ChenQ, Yan SC. Network in network[EB/OL]. [2019-10-09].https: ∥www. researchgate. net/publication/259312908_Network_In_Network.
[14] SzegedyC, LiuW, Jia YQ, et al. Going deeper with convolutions[C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12,2015, Boston, MA, USA. New York: IEEE, 2015: 1- 9.
[15] Glorot X, Bengio Y. Understanding the difficulty of training deep feedforward neural networks[J]. Journal of Machine Learning Research, 2010, 9: 249-256.
[16] He KM, Zhang XY, Ren SQ, et al. Deep residual learning for image recognition[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 770- 778.
[17] 张婷, 李玉鑑, 胡海鹤, 等. 基于跨连卷积神经网络的性别分类模型[J]. 自动化学报, 2016, 42(6): 858-865.
Zhang T, Li Y J, Hu H H, et al. A gender classification model based on cross-connected convolutional neural networks[J]. Acta Automatica Sinica, 2016, 42(6): 858-865.
[18] HuangG, Liu Z, van der Maaten L, et al. Densely connected convolutional networks[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017: 2261- 2269.
[19] Zheng W M, Zhou X Y, Zou C R, et al. Facial expression recognition using kernel canonical correlation analysis (KCCA)[J]. IEEE Transactions on Neural Networks, 2006, 17(1): 233-238.
[20] LuceyP, Cohn JF, KanadeT, et al. The extended Cohn-Kanade dataset (CK+): a complete dataset for action unit and emotion-specified expression[C]∥2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, June 13-18, 2010, San Francisco, CA, USA. New York: IEEE, 2010: 94- 101.
[21] Zhang K P, Zhang Z P, Li Z F, et al. Joint face detection and alignment using multitask cascaded convolutional networks[J]. IEEE Signal Processing Letters, 2016, 23(10): 1499-1503.
[22] 李勇, 林小竹, 蒋梦莹. 基于跨连接LeNet-5网络的面部表情识别[J]. 自动化学报, 2018, 44(1): 176-182.
Li Y, Lin X Z, Jiang M Y. Facial expression recognition withcross-connect LeNet-5 network[J]. Acta Automatica Sinica, 2018, 44(1): 176-182.
[23] Gu W F, Xiang C, Venkatesh Y V, et al. Facial expression recognition using radial encoding of local Gabor features and classifier synthesis[J]. Pattern Recognition, 2012, 45(1): 80-91.
[24] 何志超, 赵龙章, 陈闯. 用于人脸表情识别的多分辨率特征融合卷积神经网络[J]. 激光与光电子学进展, 2018, 55(7): 071503.
[25] Happy SL, RoutrayA. Robust facial expression classification using shape and appearance features[C]∥2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR), January 4-7, 2015, Kolkata, India. New York: IEEE, 2015: 1- 5.
杨旭, 尚振宏. 基于改进AlexNet的人脸表情识别[J]. 激光与光电子学进展, 2020, 57(14): 141026. Xu Yang, Zhenhong Shang. Facial Expression Recognition Based on Improved AlexNet[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141026.