[1] ZAYAS I, POMERANZ, LAI F S. Discrimination between Arthur and Arkan wheats by image analysis[J]. Cereal Chemistry, 1985,62(6):478-480.
[2] THOMSON W H, POMERANZ Y. Classification of wheat kernels using three-dimensional image analysis[J]. Cereal Chemistry, 1991,68(4):357-361.
[3] NEETHIRAJAN S, JAYAS D S, WHITE N D G. Detection of sprouted wheat kernels using soft X-ray image analysis[J]. Journal of Food Engineering, 2007,81(3):509-513.
[4] 陈丰农. 基于机器视觉的小麦并肩杂与不完善粒动态实时检测研究[D]. 杭州:浙江大学, 2012.
[5] 曹婷翠,何小海,董德良,等. 基于CNN深度模型的小麦不完善粒识别[J]. 现代计算机(专业版), 2017(36):9-14.
[6] 陈文根. 基于深度学习的小麦图谱特征技术研究[D]. 郑州:河南工业大学, 2018.
[7] 祝诗平,卓佳鑫,黄华,等. 基于CNN的小麦籽粒完整性图像检测系统[J]. 农业机械学报, 2020,51(5):36-42.
[8] LI Y, ZENG J B, SHAN S G, et al. Occlusion aware facial expression recognition using CNN with attention mechanism[J]. IEEE Transactions on Image Processing, 2019,28(5):2439-2450.
[9] WANG Z N, ZENG F W, LIU S C, et al. OAENet: Oriented attention ensemble for accurate facial expression recognition[J]. Pattern Recognition, 2021,112. DOI: 10.1016/j.patcog.2020.107694.
[10]WEN P Z, DING Y, WEN Y Y, et al. Facial expression recognition method based on convolution neural network combining attention mechanism[C]// Proceedings of the 2020 International Conference on Artificial Intelligence and Security. 2020:136-147.
[11]ZHENG W M. Multi-view facial expression recognition based on group sparse reduced-rank regression[J]. IEEE Transactions on Affective Computing, 2014,5(1):71-85.
[12]LIU Y Y, ZENG J B, SHAN S G, et al. Multi-channel pose-aware convolution neural networks for multi-view facial expression recognition[C]// Proceedings of the 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018). 2018:458-465.
[13]DIN N U, JAVED K, BAE S, et al. A novel GAN-based network for unmasking of masked face[J]. IEEE Access, 2020,8:44276-44287.〖HJ1.18mm〗
[14]SHEN X B, SUN Q S, YUAN Y H. A unified multiset canonical correlation analysis framework based on graph embedding for multiple feature extraction[J]. Neurocomputing, 2015,148:397-408.
[15]HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition[C]// Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. 2016:770-778.
[16]PENG C, ZHANG X Y, YU G, et al. Large kernel matters: Improve semantic segmentation by global convolutional network[C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. 2017:1743-1751.
[17]VASWANI A, SHAZEER N, PARMAR N, et al. Attention is all you need[C]// Proceedings of the 31st International Conference on Neural Information Processing Systems. 2017:6000-6010.
[18]CARION N, MASSA F, SYNNAEVE G, et al. End-to-end object detection with Transformers[C]// Proceedings of the 2020 European Conference on Computer Vision. 2020:213-229.
[19]师小燕,万韬阮,汤汶,等. 姿态估计算法在古建筑室内环境中的应用研究[J]. 计算机与现代化, 2012(11):214-216.
[20]MAHAPATRA D, KUANAR S, BOZORGTABAR B, et al. Self-supervised learning of inter-label geometric relationships for Gleason grade segmentation[M]// Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health. Springer, 2021:57-67.
[21]WANG Y Q, XU Z L, WANG X L, et al. End-to-end video instance segmentation with transformers[C]// Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021:8737-8746.
[22]PARK S H, LEE G, SEO J, et al. Diverse and admissible trajectory forecasting through multimodal context understanding[C]// Proceedings of the 2020 European Conference on Computer Vision. 2020:282-298.
[23]WU B C, XU C F, DAI X L, et al. Visual Transformers: Token-based image representation and processing for computer vision[J]. arXiv preprint arXiv:2006.03677, 2020.
[24]RUSSAKOVSKY O, DENG J, SU H, et al. ImageNet large scale visual recognition challenge[J]. International Journal of Computer Vision, 2015,115(3):211-252.
[25]WANG W H, XIE E Z, LI X, et al. Pyramid vision Transformer: A versatile backbone for dense prediction without convolutions[C]// Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 2021:548-558.
[26]YOU J Y, KORHONEN J. Transformer for image quality assessment[C]// Proceedings of the 2021 IEEE International Conference on Image Processing (ICIP). 2021:1389-1393.
[27]LECUN Y. LeNet-5, convolutional neural networks[DB/OL]. [2021-09-07]. http://yann.lecun.com/exdb/lenet.
[28]ALIPPI C, DISABATO S, ROVERI M. Moving convolutional neural networks to embedded systems: The AlexNet and VGG-16 case[C]// Proceedings of the 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). 2018:212-223.
[29]MAHBOD A, SCHAEFER G, WANG C L, et al. Skin lesion classification using hybrid deep neural networks[C]// Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2019:1229-1233.
[30]TAN M X, LE Q V. EfficientNet: Rethinking model scaling for convolutional neural networks[C]// Proceedings of the 36th International Conference on Machine Learning. 2019:6105-6114.
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