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浏览/检索结果: 共5条，第1-5条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Space Debris Detection Using Feature Learning of Candidate Regions in Optical Image Sequences 期刊论文 IEEE ACCESS, 2020, 卷号: 8, 页码: 150864-150877 作者:  Xi, Jiangbo;  Xiang, Yaobing;  Ersoy, Okan K.;  Cong, Ming;  Wei, Xin 收藏  |  浏览/下载：9/0  |  提交时间：2020/10/23 Space debris  Feature extraction  Machine learning  Signal to noise ratio  Object detection  Image sequences  Optical imaging  Space debris detection  background estimation  candidate region extraction  deep learning   Cascading classifier with discriminative multi-features for a specific 3D object real-time detection 期刊论文 VISUAL COMPUTER, 2019, 卷号: 35, 页码: 399-414 作者:  Wang, Rui;  Liang, Ying;  Xu, Jing Wen;  He, Zhi Hai 收藏  |  浏览/下载：4/0  |  提交时间：2019/12/30 Specific 3D object detection  Candidate extraction  Candidate region recognition  Discriminative multi-features  Cascaded classifiers   The Cat's Eye Effect Target Recognition Method Based on Visual Attention 期刊论文 Chinese Journal of Electronics, 2019, 卷号: 28, 期号: 5, 页码: 1080-1086 作者:  X.B.Wang;  J.Zhang;  S.H.Wang 收藏  |  浏览/下载：1/0  |  提交时间：2020/08/24 feature extraction,image fusion,object detection,target-saliency map,target region,Cat's eye effect target recognition method,visual,attention,second-directional derivative filter,directional channels,morphological method,potential targets exist,designed saliency fusing,method,candidate targets,Cat's eye effect target recognition method,based on visual attention (CTRVA),Target recognition,Saliency map,Engineering   The Cat's Eye Effect Target Recognition Method Based on Visual Attention 期刊论文 Chinese Journal of Electronics, 2019, 卷号: 28, 期号: 5, 页码: 1080-1086 作者:  X.B.Wang;  J.Zhang;  S.H.Wang 收藏  |  浏览/下载：1/0  |  提交时间：2020/08/24 feature extraction,image fusion,object detection,target-saliency map,target region,Cat's eye effect target recognition method,visual,attention,second-directional derivative filter,directional channels,morphological method,potential targets exist,designed saliency fusing,method,candidate targets,Cat's eye effect target recognition method,based on visual attention (CTRVA),Target recognition,Saliency map,Engineering   Features extraction and matching of teeth image based on the SIFT algorithm (EI CONFERENCE) 会议论文 2012 2nd International Conference on Computer Application and System Modeling, ICCASM 2012, July 27, 2012 - July 29, 2012, Shenyang, China Wang X.; Li H.; Dong N. 收藏  |  浏览/下载：22/0  |  提交时间：2013/03/25 Using of SIFT algorithm in the image of teeth model  can detect the features of the teeth image effectively. In this approach  first  search over all scales and image locations by using a difference-of-Gaussian function to identify potential interest points that are invariant to scale and orientation. Second  select keypoints based on measures of their stability and a detailed model is fit to determine location and scale at each candidate location. Third  assign one or more orientations to each keypoint location based on local image gradient directions. Last  measure the local image gradients at the selected scale in the region around each keypoint. And then use the KNN algorithm to match the features. Through lots of experiments and comparing with other feature extraction methods  this method can detect the features of the teeth model effectively  and offer some available parameters for 3D reconstruction of the teeth model. the authors.