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HALF-LIVES OF THIRTEEN DOUBLE beta(-)-DECAY CANDIDATES WITH TWO NEUTRINOS 会议论文
作者:  Ren, Yuejiao;  Ren, Zhongzhou
收藏  |  浏览/下载：11/0  |  提交时间：2018/08/20
Ship candidates extraction for optical color imagery 会议论文
5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Imaging Sensors and Applications, Beijing, PEOPLES R CHINA, 2013-01-01
作者:  Yu, Xinran;  Shi, Zhenwei
收藏  |  浏览/下载：6/0  |  提交时间：2020/01/06
integral distinguishers of jh and gr?stl-512 会议论文
Journal of Electronics (China)
Li Yanjun; Wu Wenling; Dong Le
收藏  |  浏览/下载：16/0  |  提交时间：2013/09/22
practical rebound attack on 12-round cheetah-256 会议论文
12th International Conference on Information Security and Cryptology, Seoul, SOUTH KOREA, DEC 02-04,
Wu Shuang; Feng Dengguo; Wu Wenling
收藏  |  浏览/下载：9/0  |  提交时间：2011/03/31
near-collisions on the reduced-round compression functions of skein and blake 会议论文
Cryptology and Network Security 9th International Conference, CANS 2010, Kuala Lumpur Malaysia, 2010
Su Bozhan; Wu Wenling; Wu Shuang; Dong Le
收藏  |  浏览/下载：13/0  |  提交时间：2011/03/31
cryptanalysis of the lane hash function 会议论文
16th Annual International Workshop on Selected Areas Cryptography, Calgary, CANADA, AUG 13-14,
Wu Shuang; Feng Dengguo; Wu Wenling
收藏  |  浏览/下载：8/0  |  提交时间：2011/03/20
Affine object recognition and affine parameters estimation based on covariant matrix (EI CONFERENCE) 会议论文
2008 International Symposium on Information Science and Engineering, ISISE 2008, December 20, 2008 - December 22, 2008, Shanghai, China
Ji H.; Li G.; Wang Y.
收藏  |  浏览/下载：28/0  |  提交时间：2013/03/25
A new method of affine object recognition and affine parameters estimation is presented. For a real-time image and a group of templates  in addition  firstly  on the basis of correct recognition  we segment the object regions in them and compute their covariant matrices. Secondly  it can estimate affine parameters exactly  normalize the ellipse regions defined by covariant matrices to circle regions to get rotational invariants  and the estimated error is within 3%. 2008 IEEE.  and compute the similarity function value between rotational invariants of real-time image and every template respectively. Then compare the values with threshold set in advance  if more than one value is larger than threshold  take the corresponding templates as candidates  and compute affine matrix between real-time image and every candidate. Finally  transform the realtime image with every affine matrix and match the result with corresponding candidate by classical matching methods. Experimental results show that the presented method is robust to illumination  with low computational complexity  and it can realize recognition of different affine objects  
Real time tracking by LOPF algorithm with mixture model (EI CONFERENCE) 会议论文
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, November 15, 2007 - November 17, 2007, Wuhan, China
Meng B.; Zhu M.; Han G.; Wu Z.
收藏  |  浏览/下载：21/0  |  提交时间：2013/03/25
A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently  we first use Sobel algorithm to extract the profile of the object. Then  we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones  in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise  the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here  we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.  
A stereo matching method based on kernel density estimation 会议论文
IEEE International Conference on Information Acquisition, AUG 20-23, 2006
作者:  Niu, Jun;  Song, Rui;  Li, Yibin
收藏  |  浏览/下载：1/0  |  提交时间：2019/12/31
A stereo matching method based on kernel density estimation 会议论文
2006 IEEE International Conference on Information Acquisition, ICIA 2006, 20 August 2006 through 23 August 2006
作者:  Niu, Jun;  Song, Rui;  Li, Yibin
收藏  |  浏览/下载：3/0  |  提交时间：2019/12/31

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