中国科学院机构知识库网格系统: 检索

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	Accelerated LiDAR data processing algorithm for self-driving cars on the heterogeneous computing platform 期刊论文 OAI收割 IET COMPUTERS AND DIGITAL TECHNIQUES, 2020, 卷号: 14, 期号: 5, 页码: 201-209 作者: Li, Wei; Liang, Jun; Zhang, Yunquan; Jia, Haipeng; Xiao, Lin \| 收藏 \| 浏览/下载：64/0 \| 提交时间：2020/12/10 feature extraction optical radar optimisation optical information processing traffic engineering computing mobile robots automobiles accelerated LiDAR data processing algorithm self-driving cars heterogeneous computing platform optimisation NVIDIA Tegra X2 computing platform feature extraction obstacle clustering
	Image Clustering Based on Multi-Scale Deep Maximize Mutual Information and Self-Training Algorithm 期刊论文 OAI收割 IEEE ACCESS, 2020, 卷号: 8, 页码: 160285-160296 作者: Yu SQ(余思泉); Shen GP(沈贵萍); Wang PY(王佩瑶); Wang YN(王宇宁); Wu CD(吴成东) \| 收藏 \| 浏览/下载：30/0 \| 提交时间：2020/10/06 Clustering algorithms Mutual information Image representation Neural networks Clustering methods Feature extraction Task analysis Representation learning image clustering mutual information maximization self-training algorithm
	A cooperative spectrum sensing method based on information geometry and fuzzy c-means clustering algorithm 期刊论文 OAI收割 EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2019, 页码: 12 作者: Zhang, Shunchao; Wang, Yonghua; Li, Jiangfan; Wan, Pin; Zhang, Yongwei \| 收藏 \| 浏览/下载：44/0 \| 提交时间：2019/07/12 Cooperative spectrum sensing Information geometry Decomposition and recombination Fuzzy c-means clustering algorithm
	A Multi-Antenna Spectrum Sensing Scheme Based on Main Information Extraction and Genetic Algorithm Clustering 期刊论文 OAI收割 IEEE ACCESS, 2019, 卷号: 7, 页码: 119620-119630 作者: Zhuang, Jiawei; Wang, Yonghua; Zhang, Shunchao; Wan, Pin; Sun, Chenhao \| 收藏 \| 浏览/下载：36/0 \| 提交时间：2020/03/30 Spectrum sensing principal component analysis information fusion genetic algorithm clustering
	An integrative hierarchical stepwise sampling strategy for spatial sampling and its application in digital soil mapping SCI/SSCI论文 OAI收割 2013 作者: Pei T.; Yang L. 收藏 \| 浏览/下载：44/0 \| 提交时间：2014/12/24 spatial sampling fuzzy clustering digital soil mapping SoLIM design information variables algorithm optimization prediction knowledge schemes model
	Automatic bridge extraction for optical images (EI CONFERENCE) 会议论文 OAI收割 6th International Conference on Image and Graphics, ICIG 2011, August 12, 2011 - August 15, 2011, Hefei, Anhui, China Gu D.-Y.; Zhu C.-F.; Shen H.; Hu J.-Z.; Chang H.-X. 收藏 \| 浏览/下载：39/0 \| 提交时间：2013/03/25 This paper describes a novel hierarchy algorithm for extracting bridges over water in optical images. To reduce the omission of bridges by searching the edge we extract the river regions which the bridges are included in. Firstly we segment the optical image to get the coarse water bodies using iterative threshold eliminate the noise regions and add the missing regions based on k-means clustering with texture information and spatial coherence. Then the blanks are connected based on shape features and candidate bridge regions are segmented from river regions. Finally the bridges are verified by geometric information and the ubiety between bridges and river. The results show that this approach is efficient and effective for extracting bridges in satellite image from Google Earth and in aerial optical images acquired by unmanned aerial vehicle. 2011 IEEE.
	Studies on information clustering algorithm based on MID 期刊论文 OAI收割 CHINESE JOURNAL OF ELECTRONICS, 2006, 卷号: 15, 期号: 4A, 页码: 918-920 作者: Ding Shifei; Shi Zhongzhi \| 收藏 \| 浏览/下载：25/0 \| 提交时间：2019/12/16 information theory measure of diversity information clustering algorithm measure of increment of diversity data processing
	A segment detection method based on improved Hough transform (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Yao Z.-J. 收藏 \| 浏览/下载：30/0 \| 提交时间：2013/03/25 Hough transform is recognized as a powerful tool in shape analysis which gives good results even in the presence of noise and the disconnection of edge. However 3. applying the standard Hough transform equation to every point of the input image edge 4. according to the local threshold 6. merging the segments whose extreme points are near. Experiment results show the approach not only can recognize regular geometric object but also can extract the segment feature of real targets in complex environment. So the proposed method can be used in the target detection of complicated scenes traditional Hough transform can only detect the lines 2. quantizing the parameter space and extracting a group of maximums according to the global threshold eliminating spurious peaks which are caused by the spreading effects and will improve the precision of tracking. cannot give the endpoints and length of the line segments and it is vulnerable to the quantization errors. Based on the analysis of its limitations Hough transform has been improved in order to detect line segment feature of targets. The algorithm aims to avoid the loss of spatial information as well as to eliminate the spurious peaks and fix on the line segments endpoints accurately 5. fixing on the endpoints of the segments according to the dynamic clustering rule which can expediently be used for the description and classification of regular objects. The method consists of 6 steps: 1. setting up the image parameter and line-segment spaces
	An Information Similarity Based Clustering Algorithm in Wireless Sensor Network 会议论文 OAI收割 2006 International Conference on Informatics and Control Technologies (ICT), Shenzhen, China, December 7-8 , 2006 作者: Liang Y(梁英); Yu HB(于海斌); Zeng P(曾鹏); Liang W(梁炜) 收藏 \| 浏览/下载：49/0 \| 提交时间：2012/10/16 Wireless sensor network clustering algorithm information similarity data aggregation genetic algorithm