[1] ZHENG Weicheng,LI Xuewei,LIU Hongzhe,et al.Fatigue driving detection algorithm based on deep learning[J].Computer Engineering,2020,46(7):21-29.(in Chinese)郑伟成,李学伟,刘宏哲,等.基于深度学习的疲劳驾驶检测算法[J].计算机工程,2020,46(7):21-29. [2] XIA Hansheng,SHEN Huan,HU Wei.Detecting distraction of drivers using human pose keypoints[J].Computer Technology and Development,2019,29(7):1-5.(in Chinese)夏瀚笙,沈峘,胡委.基于人体关键点的分心驾驶行为识别[J].计算机技术与发展,2019,29(7):1-5. [3] TANG Hui,WANG Qing,CHEN Hong,et al.Somatosensory interaction method based on deep learning[J].Computer and Modernization,2019(2):7-14.(in Chinese)唐晖,王庆,陈洪,等.基于深度学习的体感交互方法[J].计算机与现代化,2019(2):7-14. [4] WANG Tao,WANG Hongzhang,XIA Yi,et al.Human gait recognition based on convolutional neural network and attention model[J].Chinese Journal of Sensors and Actuators,2019,32(7):1027-1033.(in Chinese)汪涛,汪泓章,夏懿,等.基于卷积神经网络与注意力模型的人体步态识别[J].传感技术学报,2019,32(7):1027-1033. [5] CAO Z,SIMON T,WEI S E,et al.OpenPose:realtime multi-person 2D pose estimation using part affinity fields[C]//Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2017:7291-7299. [6] CHEN Y,SHEN C,WEI X S,et al.Adversarial PoseNet:a structure-aware convolutional network for human pose estimation[C]//Proceedings of 2017 IEEE International Conference on Computer Vision.Washington D.C.,USA:IEEE Press,2017:1212-1221. [7] FANG H S,XIE S,TAI Y W,et al.RMPE:regional multi-person pose estimation[C]//Proceedings of 2017 IEEE International Conference on Computer Vision.Washington D.C.,USA:IEEE Press,2017:2334-2343. [8] PFISTER T,CHARLES J,ZISSERMAN A.Flowing ConvNets for human pose estimation in videos[C]//Proceedings of 2015 IEEE International Conference on Computer Vision.Washington D.C.,USA:IEEE Press,2015:1913-1921. [9] XIAO Bin,WU Haiping,WEI Yichen.Simple baselines for human pose estimation and tracking[C]//Proceedings of European Conference on Computer Vision.Berlin,Germany:Springer,2018:472-487. [10] NEWELL A,YANG K,DENG J.Stacked hourglass networks for human pose estimation[C]//Proceedings of 2016 European Conference on Computer Vision.Berlin,Germany:Springer,2016:483-499. [11] WEI S,RAMAKRISHNA V,KANADE T,et al.Convolu-tional pose machines[C]//Proceedings of 2016 IEEE Con-ference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2016:483-499. [12] CHEN Yilan,WANG Zhicheng,PENG Yuxiang,et al.Cascaded pyramid network for multi-person pose estimation[EB/OL].[2019-11-10].https://arxiv.org/pdf/1711.07319.pdf. [13] SUN Ke,XIAO Bin,LIU Dong,et al.Deep high-resolution representation learning for human pose estimation[EB/OL].[2019-11-10].https://arxiv.org/pdf/1902.09212.pdf. [14] ZOPH B,VASUDEVAN V,SHLENS J,et al.Learning transferable architectures for scalable image recognition[EB/OL].[2019-11-10].https://arxiv.org/pdf/1707.07012v3.pdf. [15] LI Lingxia,WANG Yu,WU Jinjun,et al.Micro-motion hand gesture recognition method based on improved multiple dimensional convolution neural network[J].Computer Engineering,2018,44(9):243-249.(in Chinese)李玲霞,王羽,吴金君,等.基于改进型多维卷积神经网络的微动手势识别方法[J]. 计算机工程,2018,44(9):243-249. [16] GUO Jichang,WU Jie,GUO Chunle,et al.Image super-resolution reconstruction based on residual connection convolutional neural network[J].Journal of Jilin University(Engineering and Technology Edition),2019,49(5):1726-1734.(in Chinese)郭继昌,吴洁,郭春乐.基于残差连接卷积神经网络的图像超分辨率重构[J].吉林大学学报(工学版),2019,49(5):1726-1734. [17] SANDLER M,HOWARD A,ZHU M,et al.Inverted residuals and linear bottlenecks:mobile networks for classification,detection and segmentation[C]//Proceedings of 2018 IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2018:4510-4520. [18] LIN T Y,DOLLAR P,GIRSHICK R,et al.Feature pyramid networks for object detection[C]//Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2017:936-944. [19] ZHANG X,ZHOU X,LIN M,et al.ShuffleNet:an extremely efficient convolutional neural network for mobile devices[EB/OL].[2019-11-10].https://arxiv.org/pdf/1707.01083v2.pdf. [20] HOWARD A G,ZHU M L,CHEN B,et al.MobileNets:efficient convolutional neural networks for mobile vision applications[EB/OL].[2019-11-10].https://arxiv.org/pdf/1704.04861.pdf. [21] SU Zhihui,YE Ming,ZHANG Guohui,et al.Cascade feature aggregation for human pose estimation[EB/OL].[2019-11-10].https://arxiv.org/ftp/arxiv/papers/1902/1902.07837.pdf. |