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	An Improved Biologically-Inspired Image Fusion Method 期刊论文 OAI收割 International Journal of Pattern Recognition and Artificial Intelligence, 2018, 卷号: 32, 期号: 8, 页码: 20 作者: Wang, Y. Q.; Wang, Y. \| 收藏 \| 浏览/下载：24/0 \| 提交时间：2019/09/17 Image fusion rattlesnake retinex human visual system color-vision ir Computer Science
	A distributed computational cognitive model for object recognition 期刊论文 OAI收割 SCIENCE CHINA-INFORMATION SCIENCES, 2013, 卷号: 56, 期号: 9 作者: Liu YongJin; Fu QiuFang; Liu Ye; Fu XiaoLan 收藏 \| 浏览/下载：29/0 \| 提交时间：2015/05/19 distributed cognition computational model object recognition human vision system
	Computer simulation research on cognitive mechanism of human vision (EI CONFERENCE) 会议论文 OAI收割 International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2010, March 13, 2010 - March 14, 2010, Changsha, China Ke H.; You W. 收藏 \| 浏览/下载：38/0 \| 提交时间：2013/03/25 The development of intelligent system which accorded with human cognitive mechanism will exert a profound influence on national defense economy education culture and etc. A computer simulation method according with cognitive mechanism of human vision was proposed on the basis of Structural Decomposition Theory. Many basic shape feature information tables of similar object from different side can determine a kind of object uniquely. System weighted basic shape features in two different information tables by membership degree and then calculated similarity. The identifying object which had the maximum similarity with it in system was what we needed. The system used 83 pictures of 6 kinds of objects with different side for training and testing. The experiment results demonstrated task of basic shape extraction object recognition and others can be completed effectively with the method in paper. The method in paper can be a new attempt on computer simulation method according with cognitive mechanism of human vision from cognitive field. 2010 Crown Copyright.
	An intelligent video surveillance system (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on E-Product E-Service and E-Entertainment, ICEEE2010, November 7, 2010 - November 9, 2010, Henan, China Gao S. 收藏 \| 浏览/下载：16/0 \| 提交时间：2013/03/25 This paper presents an intelligent video surveillance system. The system is composed of one or more nodes flexibly according to the application scenarios such as private properties banks and museums. Each node is an autonomous vision-based device capable to perform intelligent tasks. It is able to digitize and compress the acquired analog video signals in MPEG-4 standard and then transmit the compressed video stream to the control center. At the same time the node makes use of a statistical approach for real-time detecting moving object and online alarm generation to enable a single human operator to monitor activities over a complex area using a distributed network of active video sensors. The node is implemented on a platform with high performance to ensure that the algorithm is able to run in real-time. Applications demonstrate that the intelligent system has an excellent performance in many scenarios to help people make decisions more accurately and rapidly. 2010 IEEE.
	Analysis and design of No-Reference Image Quality Assessment (EI CONFERENCE) 会议论文 OAI收割 2008 International Conference on MultiMedia and Information Technology, MMIT 2008, December 30, 2008 - December 31, 2008, Three Gorges, China 作者: Wang L.; Wang L.; Wang L. 收藏 \| 浏览/下载：15/0 \| 提交时间：2013/03/25 No-Reference (NR) Image Quality Assessment (IQA) seeks to assign quality scores that are consistent with human perception but without an explicit comparison with the reference image. Unfortunately the field of NR IQA has been largely unexplored. The basic problems in NR IQA are discussed in this paper. and several methods used in NR IQA are explained and analyzed. Finally an overall NR IQA method is designed. It should be a synthetical index which applying fuzzy measures and fuzzy integrals incorporating Human Vision System (HVS) characteristics and adhering to the philosophy of quantifying quality through blind distortion measurement. 2008 IEEE.