[1] [1] Xie Xingxing, Cheng Gong, Wang Jiabao, et al. iented rcnn f object detection[C]Proceedings of the IEEECVF International Conference on Computer Vision, 2021: 35203529.

[2] Yunzheng Su, Qun Hao, Jie Cao, et al. Point cloud semantic segmentation method based on segmented blocks merging. Infrared and Laser Engineering, 50, 20200482(2021).

[3] Weipeng Li, Xiaogang Yang, Chuanxiang Li, et al. An improved semi-supervised transfer learning method for infrared object detection neural network. Infrared and Laser Engineering, 50, 20200511(2021).

[4] Shifeng Zhang, Cheng Chi, Zhen Lei, et al. Refineface: Refinement neural network for high performance face detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43, 4008-4020(2020).

[5] [5] Meng Qiang, Zhao Shichao, Huang Zhida, et al. Magface: A universal representation f face recognition quality assessment[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2021: 1422514234.

[6] S M A Abdullah, S Y A Ameen, M A Sadeeq, et al. Multimodal emotion recognition using deep learning. Journal of Applied Science and Technology Trends, 2, 52-58(2021).

[7] Yunfeng Wang, Zuopeng Li. Application research of object detection algorithm in edge environment. Computer Engineering and Applications, 57, 220-228(2021).

[8] [8] Li Hao, Kadav Asim, Durdanovic Ig, et al. Pruning filters f efficient convs [EBOL]. (20160831) [20220309]. https:arxiv.gabs1608.08710.

[9] [9] Li Zhisheng, Wang Lei, Guo Shasha, et al. Laius: An 8bit fixedpoint CNN hardware inference engine[C]2017 IEEE International Symposium on Parallel Distributed Processing with Applications 2017 IEEE International Conference on Ubiquitous Computing Communications (ISPAIUCC), 2017: 143150.

[10] [10] Courbariaux Matthieu, Hubara Itay, Soudry Daniel, et al. Binarized neural wks: Training deep neural wks with weights activations constrained to +1 1 [EBOL].(20160209)[20220309]. https:arxiv.gabs1602.02830.

[11] Alex Krizhevsky, Ilya Sutskever, Geoffrey E Hinton. Imagenet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems, 25, 1097-1105(2012).

[12] [12] Liu Zechun, Shen Zhiqiang, Savvides Marios, et al. React: Towards precise binary neural wk with generalized activation functions[C]European Conference on Computer Vision, 2020: 143159.

[13] [13] Liu Wei, Anguelov Dragomir, Erhan Dumitru, et al. Ssd: Single shot multibox detect[C]European Conference on Computer Vision, 2016. SPRINGER: 2137.

[14] Shaoqing Ren, Kaiming He, Ross Girshick, et al. Faster r-cnn: Towards real-time object detection with region proposal networks. Advances in Neural Information Processing Systems, 28, 91-99(2015).

[15] [15] Howard rew G, Zhu Menglong, Chen Bo, et al. Mobiles: Efficient convolutional neural wks f mobile vision applications [EBOL]. (20170417)[20220309]. https:arxiv.gabs1704.04861v1.

[16] [16] Gao ShangHua, Han Qi, Li Duo, et al. Representative batch nmalization with feature calibration[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2021: 86698679.

[17] [17] Zhuang Fuzhen, Qi Zhiyuan, Duan Keyu, et al. A comprehensive survey on transfer learning [C]Proceedings of the IEEE, 2020, 109(1): 4376.

[18] [18] Yang Shuo, Luo Ping, Loy ChenChange, et al. Wider face: A face detection benchmark[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2016: 55255533.

[19] [19] Jain Vidit, LearnedMiller Erik. FDDB: A benchmark f face detection in unconstrained settings [R]. UMass Amherst Technical Rept, 2010.

[20] [20] Huang Gary B, Mattar Marwan, Berg Tamara, et al. Labeled faces in the wild: A database fstudying face recognition in unconstrained environments[C]Wkshop on Faces in ''RealLife'' Images: Detection, Alignment, Recognition, 2008.

[21] Connor Shorten, Taghi M Khoshgoftaar. A survey on image data augmentation for deep learning. Journal of Big Data, 6, 1-48(2019).