中国科学院机构知识库网格系统: 检索

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	Distinguishing Epileptiform Discharges From Normal Electroencephalograms Using Scale-Dependent Lyapunov Exponent 期刊论文 OAI收割 FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, 2020, 卷号: 8, 页码: 14 作者: Li, Qiong; Gao, Jianbo; Huang, Qi; Wu, Yuan; Xu, Bo \| 收藏 \| 浏览/下载：48/0 \| 提交时间：2021/01/07 EEG epileptiform discharges power spectral density (PSD) scale-dependent Lyapunov exponent (SDLE) random forest classifier support vector machine (SVM)
	Mapping Mangrove Forests Based on Multi-Tidal High-Resolution Satellite Imagery 期刊论文 OAI收割 REMOTE SENSING, 2018, 卷号: 10, 期号: 9, 页码: 20 作者: Xia, Qing; Qin, Cheng-Zhi; Li, He; Huang, Chong; Su, Fen-Zhen \| 收藏 \| 浏览/下载：41/0 \| 提交时间：2019/05/23 mangrove forest mapping high-resolution satellite imagery tide SVM classifier spectral signature
	Mapping Mangrove Forests Based on Multi-Tidal High-Resolution Satellite Imagery 期刊论文 OAI收割 REMOTE SENSING, 2018, 卷号: 10, 期号: 9, 页码: 20 作者: Xia, Qing \| 收藏 \| 浏览/下载：33/0 \| 提交时间：2019/05/23 mangrove forest mapping high-resolution satellite imagery tide SVM classifier spectral signature
	Mapping Mangrove Forests Based on Multi-Tidal High-Resolution Satellite Imagery 期刊论文 OAI收割 REMOTE SENSING, 2018, 卷号: 10, 期号: 9, 页码: 20 作者: Xia, Qing; Qin, Cheng-Zhi; Li, He; Huang, Chong; Su, Fen-Zhen \| 收藏 \| 浏览/下载：42/0 \| 提交时间：2019/05/23 mangrove forest mapping high-resolution satellite imagery tide SVM classifier spectral signature
	Classifying Discriminative Features for Blur Detection 期刊论文 OAI收割 ieee transactions on cybernetics, 2016, 卷号: 46, 期号: 10, 页码: 2220-2227 作者: Pang, Yanwei; Zhu, Hailong; Li, Xinyu; Li, Xuelong 收藏 \| 浏览/下载：31/0 \| 提交时间：2016/11/02 Blur detection classifier feature extraction motion blur support vector machine (SVM)
	Person-specific named entity recognition using SVM with rich feature sets 期刊论文 OAI收割 chinese journal of library and information science, 2012, 卷号: 5, 期号: 3, 页码: 27-46 NIE Hui 收藏 \| 浏览/下载：53/0 \| 提交时间：2012/11/29 Named entity recognition Natural language processing SVM-based classifier Feature selection
	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：73/0 \| 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.
	A SVM-based classifier with shape and motion features for a pedestrian detection system 会议论文 OAI收割 IEEE Intelligent Vehicles Symposium, Meguroku, JAPAN, JUN 13-15, 2006 作者: Chen, D.; Cao, X. B.; Xu, Y. X.; Qiao, H.; Wang, F. Y. 收藏 \| 浏览/下载：25/0 \| 提交时间：2017/01/13 image classification / image motion analysis / object detection / support vector machines / traffic engineering computing / SVM-based classifier / decomposed SVM algorithm / motion features / pedestrian detection system / shape features