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[2] GuangMing Zhu, Liang Zhang, et al. Continuous Gesture Segmentation and Recognition using 3DCNN and Convolutional LSTM[J]. IEEE Transaction on Multimedia, 2019, 21(4):1011-1021, SCI WOS:000462413700016, II区.

[3] GuangMing Zhu, Liang Zhang, et al. Multimodal Gesture Recognition Using 3-D Convolution and Convolutional LSTM[J]. IEEE ACCESS, 2017, 5:4517-4524, SCI WOS: 000402940400068, II区.

[4] GuangMing Zhu, Liang Zhang, et al. An Online Continuous Human Action Recognition Algorithm Based on the Kinect Sensor[J]. Sensors, 2016, 16(2), SCI WOS: 000371787800077, III区.

[5] GuangMing Zhu, Liang Zhang, et al. Human action recognition using multi-layer codebooks of key poses and atomic motions[J]. Signal Processing-Image Communication, 2016, 42, SCI WOS: 000371939600002, III区.

[6] GuangMing Zhu, Fan Zhou, et al. A nonlinear smoother for target tracking in asynchronous wireless sensor networks[J]. Digital Signal Processing, 2015, 41, SCI WOS: 000354230700003, III区.

[1] Liang Zhang, Guangming Zhu*, et al. Attention in Convolutional LSTM for Gesture Recognition[C]. NIPS 2018, 2018:  A类国际会议.

[2] Liang Zhang, Guangming Zhu*, et al. Learning Spatiotemporal Features using 3DCNN and Convolutional LSTM for Gesture Recognition[C]. ICCV 2017, 2017: 3120-3128, WSO: 00042523960302, A类国际会议.

[3] Guangming Zhu, Liang Zhang, et al. Large-scale Isolated Gesture Recognition using pyramidal 3D convolutional networks[C]. ICPR 2016, 2016: 19-24, EI: 20171903659819, C类国际会议.

[4] Guangming Zhu, Liang Zhang, et al. Human action recognition using key poses and atomic motions[C]. IEEE-ROBIO 2015, 2015: 1209-1214, EI: 20161802327539.