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Multimodal Gait Recognition for Neurodegenerative Diseases

Autor: Zhao, Aite, Li, Jianbo, Dong, Junyu, Qi, Lin, Zhang, Qianni, Li, Ning, Wang, Xin, Zhou, Huiyu

In recent years, single modality based gait recognition has been extensively explored in the analysis of medical images or other sensory data, and it is recognised that each of the established approaches has different strengths and weaknesses. As an

Externí odkaz: http://arxiv.org/abs/2101.02469

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Associated Spatio-Temporal Capsule Network for Gait Recognition

Autor: Zhao, Aite, Dong, Junyu, Li, Jianbo, Qi, Lin, Zhou, Huiyu

It is a challenging task to identify a person based on her/his gait patterns. State-of-the-art approaches rely on the analysis of temporal or spatial characteristics of gait, and gait recognition is usually performed on single modality data (such as

Externí odkaz: http://arxiv.org/abs/2101.02458

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Muti-view Mouse Social Behaviour Recognition with Deep Graphical Model

Autor: Jiang, Zheheng, Zhou, Feixiang, Zhao, Aite, Li, Xin, Li, Ling, Tao, Dacheng, Li, Xuelong, Zhou, Huiyu

Home-cage social behaviour analysis of mice is an invaluable tool to assess therapeutic efficacy of neurodegenerative diseases. Despite tremendous efforts made within the research community, single-camera video recordings are mainly used for such ana

Externí odkaz: http://arxiv.org/abs/2011.02451

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Perceptual underwater image enhancement with deep learning and physical priors

Autor: Chen, Long, Jiang, Zheheng, Tong, Lei, Liu, Zhihua, Zhao, Aite, Zhang, Qianni, Dong, Junyu, Zhou, Huiyu

Underwater image enhancement, as a pre-processing step to improve the accuracy of the following object detection task, has drawn considerable attention in the field of underwater navigation and ocean exploration. However, most of the existing underwa

Externí odkaz: http://arxiv.org/abs/2008.09697

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