中国科学院机构知识库网格系统: 检索

Streaming Data Collection With a Private Sketch-Based Protocol 期刊论文 OAI收割
IEEE INTERNET OF THINGS JOURNAL, 2024, 卷号: 11, 期号: 15, 页码: 25950-25967
作者: Li, Ying; Lee, Xiaodong; Peng, Botao; Palpanas, Themis; Xue, Jingan

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收藏 | 浏览/下载：4/0 | 提交时间：2024/12/06

Privacy Estimation Data collection Frequency estimation Protocols Protection Internet local differential privacy (LDP) mean estimation sketch

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

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收藏 | 浏览/下载：54/0 | 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

Evidence for diurnal periodicity of earthquakes from midnight to daybreak 期刊论文 OAI收割
NATIONAL SCIENCE REVIEW, 2019, 卷号: 6, 期号: 5, 页码: 1016-1023
作者: Hao, Jinlai; Zhang, Jinhai; Yao, Zhenxing

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收藏 | 浏览/下载：15/0 | 提交时间：2020/05/18

periodicity of earthquakes time-frequency analyses ocean tide earth tide Local Mean Time

Mean-square convergence of a symplectic local discontinuous Galerkin method applied to stochastic linear Schrodinger equation 期刊论文 OAI收割
IMA JOURNAL OF NUMERICAL ANALYSIS, 2017, 卷号: 37, 期号: 2, 页码: 1041-1065
作者: Chen, Chuchu; Hong, Jialin; Ji, Lihai

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收藏 | 浏览/下载：26/0 | 提交时间：2018/07/30

symplectic method local discontinuous Galerkin method stochastic linear Schrodinger equation L-2-stability charge conservation law mean-square convergence

Efficient and Robust Learning for Sustainable and Reacquisition-Enabled Hand Tracking 期刊论文 OAI收割
ieee transactions on cybernetics, 2016, 卷号: 46, 期号: 4, 页码: 945-958
作者: Aziz, Muhammad Ali Abdul; Niu, Jianwei; Zhao, Xiaoke; Li, Xuelong

收藏 | 浏览/下载：32/0 | 提交时间：2016/08/18

Computer vision histograms of oriented gradient (HOG) local binary pattern (LBP) machine learning mean shift implanted particle filter

A tracking method with structural local mean and local standard deviation appearance model 会议论文 OAI收割
全国模式识别学术会议(6th Chinese Conference on Pattern Recognition), 湖南长沙, 2014年11月17-19
作者: Yang DW(杨大为); Cong Y(丛杨); Tang YD(唐延东); Li, Yulian

收藏 | 浏览/下载：31/0 | 提交时间：2014/12/29

object tracking local mean local standard deviation structural appearance model the Native Bayesian

Forward-Backward Mean-Shift for Visual Tracking With Local-Background-Weighted Histogram 期刊论文 OAI收割
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2013, 卷号: 14, 期号: 3, 页码: 1480-1489
作者: Wang, Lingfeng; Yan, Hongping; Wu, Huai-Yu; Pan, Chunhong

收藏 | 浏览/下载：44/0 | 提交时间：2015/08/12

Forward-backward mean shift (FBMS) local-background-weighted histogram (LBWH) visual tracking

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：59/0 | 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).

图像特征检测与匹配研究 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, 2008
作者: 王志衡

收藏 | 浏览/下载：84/0 | 提交时间：2015/09/02

特征检测特征匹配伪球滤波器内积能量局部方向分布均值标准差描述子直线匹配曲线匹配 feature detection feature matching pseudosphere filter local orientation distribution mean standard deviation descriptor line matching curve matching

A note on the convergence of the mean shift 期刊论文 OAI收割
PATTERN RECOGNITION, 2007, 卷号: 40, 期号: 6, 页码: 1756-1762
作者: Li, Xiangru; Hu, Zhanyi; Wu, Fuchao

收藏 | 浏览/下载：15/0 | 提交时间：2015/11/08

mean shift convergence local structure computer vision