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8篇 您的检索式：作者名="Canhui Cai"

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		题名	作者	年代	出处	被引量
	1	Joint horizontal and vertical deep learning feature for vehicle re-identification显示文摘Dear editor,Vehicle re-identification is a procedure in which a query image of a vehicle can be matched to vehicle images captured by different cameras in a data gallery.This procedure is extremely important for the improvement of public safety;however,accurately re-identifying vehicles is a very challenging computer vision task because vehicle images are captured from different camera view-points and they usually contain large variations in appearances.Therefore,the development of an effective vehicle re-identification method is both challenging and socially meaningful.	Jianqing ZHU Huanqiang ZENG Xin JIN Yongzhao DU Lixin ZHENG Canhui CAI	2019	Science China(Information Sciences)2019，62，9：	4
	2	Comparison of physicochemical properties of starches from seed and rhizome of lotus显示文摘	Jianmin Man Jinwen Cai Canhui Cai Bin Xu Huyin Huai Cunxu Wei	2012	Carbohydrate Polymers2012，，2：	1
	3	Fast Multiview Video Coding Using Adaptive Prediction Struc- ture and Hierarchical Mode Decision显示文摘	Zeng Huanqiang 、Wang Xiaolan Cai Canhui	2014	IEEE Transac- tions on Circuits and Systems for Video Technology2014，24，9：	1
	4	In Situ Gelation of Starch Using Hot Stage Microscopy显示文摘	Cai Canhui Cai Jinwen Zhao Lingxiao	2014	Food Sci Biotechnol2014，23，1：	1
	5	Morpholo- gy, Structure and Gelatinization Properties of Hetero- geneous Starch Granules from High-amylose Maize显示文摘	Cai Canhui Zhao Lingxiao Huang Jun	2014	Carbohydrate Polymlers2014，，102：	1
	6	Prediction-Compensated Polyphase Multiple Description Image Coding with Adaptive Redundancy Control显示文摘	Zhe Wei Kai Kuang Ma Canhui Cai	2012	IEEE Transactions on Circuits and Systems for Video Technology2012，22，3：	1
	7	Physicochemical properties of rhizome starch from a traditional Chinese medicinal plant of Anemone altaica 显示文摘	Man Jianmin Cai Jinwen Cai Canhui	2012	Carbohydrate Polymers2012，89，2：	1
	8	Pedestrian attribute classification with multi-scale and multi-label convolutional neural networks显示文摘Pedestrian attribute classification from a pedestrian image captured in surveillance scenarios is challenging due to diverse clothing appearances,varied poses and different camera views. A multiscale and multi-label convolutional neural network( MSMLCNN) is proposed to predict multiple pedestrian attributes simultaneously. The pedestrian attribute classification problem is firstly transformed into a multi-label problem including multiple binary attributes needed to be classified. Then,the multi-label problem is solved by fully connecting all binary attributes to multi-scale features with logistic regression functions. Moreover,the multi-scale features are obtained by concatenating those featured maps produced from multiple pooling layers of the MSMLCNN at different scales. Extensive experiment results show that the proposed MSMLCNN outperforms state-of-the-art pedestrian attribute classification methods with a large margin.	朱建清 Zeng Huanqiang Zhang Yuzhao Zheng Lixin Cai Canhui	2018	High Technology Letters2018，24，1：	0

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