机构

• 长春光学精密机械与物... [6]
• 自动化研究所 [5]
• 计算技术研究所 [2]
• 西安光学精密机械研究... [2]
• 高能物理研究所 [1]
• 沈阳自动化研究所 [1]
• 更多

采集方式

• OAI收割 [18]

内容类型

• 期刊论文 [9]
• 会议论文 [8]
• 学位论文 [1]

发表日期

• 2023 [1]
• 2022 [2]
• 2019 [2]
• 2017 [4]
• 2013 [1]
• 2011 [3]
• 更多

学科主题

筛选

浏览/检索结果: 共18条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Spectral-Spatial Attention Rotation-Invariant Classification Network for Airborne Hyperspectral Images 期刊论文  OAI收割 DRONES, 2023, 卷号: 7, 期号: 4 作者:  Shi, Yuetian;  Fu, Bin;  Wang, Nan;  Cheng, Yinzhu;  Fang, Jie   |  收藏  |  浏览/下载：42/0  |  提交时间：2023/05/29 airborne hyperspectral image  hyperspectral image classification  rotation-invariant  local spatial feature enhancement  convolutional neural network  attention mechanism  lightweight feature enhancement   Gradient-Aligned convolution neural network 期刊论文  OAI收割 PATTERN RECOGNITION, 2022, 卷号: 122, 页码: 10 作者:  Hao, You;  Hu, Ping;  Li, Shirui;  Udupa, Jayaram K.;  Tong, Yubing   |  收藏  |  浏览/下载：39/0  |  提交时间：2021/12/01 Gradient alignment  Rotation equivariant convolution  Rotation invariant neural network   Rotation-Invariant Attention Network for Hyperspectral Image Classification 期刊论文  OAI收割 IEEE Transactions on Image Processing, 2022, 卷号: 31, 页码: 4251-4265 作者:  Zheng, Xiangtao;  Sun, Hao;  Lu, Xiaoqiang;  Xie, Wei   |  收藏  |  浏览/下载：33/0  |  提交时间：2022/07/21 Hyperspectral image classification  convolutional neural network  rotation-invariant network  spectralspatial feature extraction  attention mechanism   3D Aided Duet GANs for Multi-View Face Image Synthesis 期刊论文  OAI收割 IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2019, 卷号: 14, 期号: 8, 页码: 2028-2042 作者:  Cao, Jie;  Hu, Yibo;  Yu, Bing;  He, Ran;  Sun, Zhenan   |  收藏  |  浏览/下载：80/0  |  提交时间：2019/07/12 Face rotation and frontalization  multi-view face synthesis  pose-invariant face recognition  face reconstruction   Rotaion and Scale-invariant Object Detector for High Resolution Optical Remote Sensing Images 会议论文  OAI收割 日本横滨, 2019年7月29日-2019年8月2日 作者:  Huang H(黄河);  Huo CL(霍春雷);  Wei FL(魏飞龙);  Pan CH(潘春洪)   |  收藏  |  浏览/下载：73/0  |  提交时间：2019/06/24 Rotation-invariant  Scale-invariant  Convolutional Neural Network  Optical Remote Sensing  Object Detection   Ordinal pyramid coding for rotation invariant feature extraction 期刊论文  OAI收割 NEUROCOMPUTING, 2017, 卷号: 242, 期号: 242, 页码: 150-160 作者:  Wang, Guoli;  Fan, Bin;  Zhou, Zhili;  Pan, Chunhong   |  收藏  |  浏览/下载：19/0  |  提交时间：2017/05/09 Rotation Invariant  Ordinal Pyramid Pooling  Fisher Vector  Feature Extraction   Feature Extraction by Rotation-Invariant Matrix Representation for Object Detection in Aerial Image 期刊论文  OAI收割 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2017, 卷号: 14, 期号: 6, 页码: 851-855 作者:  Wang, Guoli;  Wang, Xinchao;  Fan, Bin;  Pan, Chunhong   |  收藏  |  浏览/下载：34/0  |  提交时间：2017/05/09 Feature Extraction  Fisher Vector  Object Detection  Ring Pyramid Pooling (Rpp)  Rotation-invariant Matrix (Rim)   Global and Local Oriented Edge Magnitude Patterns for Texture Classification 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2017, 卷号: 31, 期号: 3, 页码: 1-13 作者:  Dong, Jun;  Yuan, Xue;  Xiong, Fanlun 收藏  |  浏览/下载：23/0  |  提交时间：2018/07/04 Texture Classification  Local Binary Pattern  Histogram Of Gradient  Rotation Invariant   A Two-Phase Improved Correlation Method for Automatic Particle Selection in Cryo-EM 期刊论文  OAI收割 IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2017, 卷号: 14, 期号: 2, 页码: 316-325 作者:  Zhang, Fa;  Chen, Yu;  Ren, Fei;  Wang, Xuan;  Liu, Zhiyong   |  收藏  |  浏览/下载：38/0  |  提交时间：2019/12/12 Particle selection  feature-based  template-matching  rotation-invariant feature  correlation score functions   A shape context based Hausdorff similarity measure in image matching 会议论文  OAI收割 5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013 作者:  Ma TL(马天磊);  Liu YP(刘云鹏);  Shi ZL(史泽林);  Yin J(尹健) 收藏  |  浏览/下载：37/0  |  提交时间：2013/12/26 The traditional Hausdorff measure, which uses Euclidean distance metric (L2 norm) to define the distance between coordinates of any two points, has poor performance in the presence of the rotation and scale change although it is robust to the noise and occlusion. To address the problem, we define a novel similarity function including two parts in this paper. The first part is Hausdorff distance between shapes which is calculated by exploiting shape context that is rotation and scale invariant as the distance metric. The second part is the cost of matching between centroids. Unlike the traditional method, we use the centroid as reference point to obtain its shape context that embodies global information of the shape. Experiment results demonstrate that the function value between shapes is rotation and scale invariant and the matching accuracy of our algorithm is higher than that of previously proposed algorithm on the MEPG-7 database.