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	Quantitative distinction of the relative actions of climate change and human activities on vegetation evolution in the Yellow River Basin of China during 1981-2019 期刊论文 OAI收割 JOURNAL OF ARID LAND, 2022, 页码: 18 作者: Liu Yifeng; Guo Bing; Lu Miao; Zang Wenqian; Yu Tao \| 收藏 \| 浏览/下载：60/0 \| 提交时间：2022/11/09 vegetation evolution driving mechanisms climate change human activities relative actions Geodetector Yellow River Basin
	Quantitative distinction of the relative actions of climate change and human activities on vegetation evolution in the Yellow River Basin of China during 1981-2019 期刊论文 OAI收割 JOURNAL OF ARID LAND, 2022, 页码: 18 作者: Liu Yifeng; Guo Bing; Lu Miao; Zang Wenqian; Yu Tao \| 收藏 \| 浏览/下载：40/0 \| 提交时间：2022/11/09 vegetation evolution driving mechanisms climate change human activities relative actions Geodetector Yellow River Basin
	Efficient Search and Localization of Human Actions in Video Databases 期刊论文 OAI收割 ieee transactions on circuits and systems for video technology, 2014, 卷号: 24, 期号: 3, 页码: 504-512 作者: Shao, Ling; Jones, Simon; Li, Xuelong 收藏 \| 浏览/下载：25/0 \| 提交时间：2015/03/18 Human actions relevance feedback spatio-temporal localization video retrieval
	Efficient human action recognition using accumulated motion image and support vector machines (EI CONFERENCE) 会议论文 OAI收割 International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011, November 19, 2011 - November 23, 2011, Suzhou, China 作者: Zhang X.; Zhang J.; Zhang J.; Zhang X.; Zhang X. 收藏 \| 浏览/下载：68/0 \| 提交时间：2013/03/25 Vision-based human action recognition provides an advanced interface and research in this field of human action recognition has been actively carried out. This paper describes a scheme for recognizing human actions from a video sequences. The proposed method is an extension of the Motion History Image(MHI) method based on the ordinal measure of accumulated motion which is robust to variations of appearances. We define the accumulated motion image(AMI) using image differences firstly. Then the AMI of the video sequencesis resized to a MN regulation following the standard of training phases. Finally we employ Support Vector Machine(SVM) as a classifier to distinguish the current activity in target video sequences. In a word our proposed algorithm not only outperforms the state of art on public available KTH data set and Weizmann data set but also proves practical to some real world applications in addition this method is computationally simple and able to achieve a satisfactory accuracy.
	Monte Carlo simulation of light propagation in human tissue models (EI CONFERENCE) 会议论文 OAI收割 3rd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2009, June 11, 2009 - June 13, 2009, Beijing, China 作者: Wang Z.; Wang L.; Wang L.; Wang L.; Wang Z. 收藏 \| 浏览/下载：35/0 \| 提交时间：2013/03/25 In this paper in order to be more sensitive to the volumetric changes of capillaries in the skin the photon propagation process in human brain tissue and skin tissue with various source and detector separation distances were simulated based on the Monte Carlo method. The human brain model and the skin model that were used in our experiments have five layers and seven layers the separation distance of source and detector should be approximately eight millimeters. Future work was discussed at the end of the paper. 2009 IEEE. respectively. The backscattered intensity from every layer of the human tissue model was obtained by marking the deepest layer that every photon can reach. The simulation results of brain model indicated that the source-detector separation distance should be selected at three centimeters for studies on the actions of the brain nerve cells