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	Research on Deep Learning Denoising Method in an Ultra-Fast All-Optical Solid-State Framing Camera 会议论文 OAI收割 Dublin, Ireland, 2021-07-19 作者: Zhou, Jian; Wang, Zhuping; Wang, Tao; Yang, Qing; Wen, Keyao \| 收藏 \| 浏览/下载：28/0 \| 提交时间：2021/09/03 Ultra-fast all-optical solid-state framing camera Convolutional neural network Non-local mean filtering Spatial resolution X-ray
	Species richness and phylogenetic diversity of different growth forms of angiosperms across a biodiversity hotspot in the horn of Africa 期刊论文 OAI收割 JOURNAL OF SYSTEMATICS AND EVOLUTION, 2020, 页码: 10 作者: Zhou, Ya-Dong; Boru, Biyansa Hirpo; Wang, Sheng-Wei; Wang, Qing-Feng \| 收藏 \| 浏览/下载：25/0 \| 提交时间：2020/10/04 environmental variable Ethiopia and Eritrea flora phylogenetic diversity woody and herbaceous
	Strong restrictions on the trait range of co-occurring species in the newly created riparian zone of the Three Gorges Reservoir Area, China 期刊论文 OAI收割 JOURNAL OF PLANT ECOLOGY, 2019, 卷号: 12, 期号: 5, 页码: 825-833 作者: Zhang, Aiying; Cornwell, Will; Li, Zhaojia; Xiong, Gaoming; Fan, Dayong \| 收藏 \| 浏览/下载：84/0 \| 提交时间：2022/01/06 flood-dry-flood neighbor distance novel ecosystem specific leaf area trait-based approach
	The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: Sun H.; Han H.-X.; Sun H. 收藏 \| 浏览/下载：50/0 \| 提交时间：2013/03/25 Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
	基于模板匹配的天体光谱自动处理方法研究学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2006 作者: 段福庆收藏 \| 浏览/下载：81/0 \| 提交时间：2015/09/02 天体光谱红移 PCA 小波变换交叉相关 Astronomical spectra redshift principal component analysis wavelet transform cross-correlation
	Mean shift based auto-extraction of spectral lines for non-emission-line objects 期刊论文 OAI收割 SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 卷号: 25, 期号: 11, 页码: 1884-1888 作者: Duan, FQ; Wu, FC; Luo, AL; Zhao, YH 收藏 \| 浏览/下载：11/0 \| 提交时间：2015/11/06