机构

• 地理科学与资源研究所 [3]
• 长春光学精密机械与物... [3]
• 自动化研究所 [3]
• 西安光学精密机械研究... [1]

采集方式

• OAI收割 [10]

内容类型

• 期刊论文 [5]
• 会议论文 [3]
• SCI/SSCI论文 [2]

发表日期

• 2025 [1]
• 2022 [1]
• 2020 [1]
• 2019 [1]
• 2018 [1]
• 2016 [2]
• 更多

学科主题

筛选

浏览/检索结果: 共10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 ACWCD: Utilizing Inherent Transformers Information and Prior Knowledge for Weakly Supervised Change Detection 期刊论文  OAI收割 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2025, 卷号: 63, 页码: 4402614 作者:  Liu, Wenhao;  Yu, Zhuoyuan;  Luo, Bin   |  收藏  |  浏览/下载：4/0  |  提交时间：2025/03/18 Cams  Transformers  Feature extraction  Neural networks  Training  Data mining  Remote sensing  Refining  Deep learning  Decoding  Change detection (CD)  class activation maps (CAMs)  deep learning  high-resolution images  multihead self-attention (MHSA)  prior knowledge  transformers  weakly supervised learning   Train in Dense and Test in Sparse: A Method for Sparse Object Detection in Aerial Images 期刊论文  OAI收割 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 卷号: 19, 页码: 5 作者:  Ding, Kun;  He, Guojin;  Gu, Huxiang;  Zhong, Zisha;  Xiang, Shiming   |  收藏  |  浏览/下载：23/0  |  提交时间：2022/02/16 Convolution  Head  Training  Testing  Object detection  Feature extraction  Real-time systems  Aerial images  object detection  sparse convolution  spatial sparsity   Online Transfer Learning for Differential Diagnosis of Benign and Malignant Thyroid Nodules With Ultrasound Images 期刊论文  OAI收割 IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2020, 卷号: 67, 期号: 10, 页码: 2773-2780 作者:  Zhou, Hui;  Wang, Kun;  Tian, Jie   |  收藏  |  浏览/下载：27/0  |  提交时间：2021/01/07 Cancer  Biological system modeling  Ultrasonic imaging  Feature extraction  Radiomics  Training  Deep learning  Diagnosis  online learning  radiomics  transfer learning  thyroid nodules  ultrasound images   Adversarial image generation by combining content and style 期刊论文  OAI收割 IET IMAGE PROCESSING, 2019, 卷号: 13, 期号: 14, 页码: 2716-2723 作者:  Liu, Songyan;  Zhao, Chaoyang;  Gao, Yunze;  Wang, Jinqiao;  Tang, Ming   |  收藏  |  浏览/下载：49/0  |  提交时间：2020/03/30 image recognition  feature extraction  learning (artificial intelligence)  image texture  adversarial image generation  unique style  reference images  style feature extraction module  style specific image generation model  double-cycle training strategy  natural-content pairs  input natural images  style exchange  style-exchanged images  licence-plate image  handbags images   A case-oriented web-based training system for breast cancer diagnosis 期刊论文  OAI收割 COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2018, 卷号: 156, 页码: 73-83 作者:  Huang, Qinghua;  Huang, Xianhai;  Liu, Longzhong;  Lin, Yidi;  Long, Xingzhang   |  收藏  |  浏览/下载：41/0  |  提交时间：2018/12/12 Breast Ultrasound Images  Medical Database  Web-based Training  Feature Scoring  Bi-rads  Computer-aided Diagnosis   Utilizing spatial association analysis to determine the number of multiple grids for multiple-point statistics SCI/SSCI论文  OAI收割 2016 作者:  Bai H. X.;  Ge, Y.;  Mariethoz, G.   |  收藏  |  浏览/下载：23/0  |  提交时间：2017/11/09 Multi-point simulation  Multiple grid simulation  Multiple grid number  Join count statistics  Single normal equation simulation  training images  simulation  geostatistics  classification  reconstruction  algorithm  objects  scale   Utilizing spatial association analysis to determine the number of multiple grids for multiple-point statistics SCI/SSCI论文  OAI收割 2016 作者:  Bai H. X.;  Ge, Y.;  Mariethoz, G. 收藏  |  浏览/下载：32/0  |  提交时间：2016/12/16 Multi-point simulation  Multiple grid simulation  Multiple grid number  Join count statistics  Single normal equation simulation  training images  simulation  geostatistics  classification  reconstruction  algorithm  objects  scale   Reality Sim: A realistic environment for robot simulation platform of humanoid robot (EI CONFERENCE) 会议论文  OAI收割 5th International Conference on Automation, Robotics and Applications, ICARA 2011, December 6, 2011 - December 8, 2011, Wellington, New zealand 作者:  Fu Y. 收藏  |  浏览/下载：37/0  |  提交时间：2013/03/25 As a virtual training  testing and evaluating environment  simulation platform becomes a significant component in Soccer Robot project. Nevertheless  the simulated environment in a simulation platform usually has a big gap with the realistic world. In order to solve this issue  we demonstrate a more realistic simulation system which is called Reality Sim with numerous real images. By this system  the computer vision code could be easily tested on simulation platform. For this purpose  previously  an image database with a large quantity of images recorded by camera pose is built. Furthermore  if the camera pose of an image is not included in the database  an interpolation algorithm is used to reconstruct a brand-new realistic image of that pose such that a realistic image could be provided on every robot camera pose. Our results show this system effectively simulates a more realistic environment for simulation platform. 2011 IEEE.   Contour extracting with combination particle filtering and em algorithm (EI CONFERENCE) 会议论文  OAI收割 International Symposium on Photoelectronic Detection and Imaging, ISPDI 2007: Related Technologies and Applications, September 9, 2007 - September 12, 2007, Beijing, China Meng B.; Zhu M. 收藏  |  浏览/下载：28/0  |  提交时间：2013/03/25 The problem of extracting continuous structures from images is a difficult issue in early pattern recognition and image processings[1]. Tracking with contours in a filtering framework requires a dynamical model for prediction. Recently  Particle filter  is widely used because its multiple hypotheses and versatility within framework. However  the good choice of the propagation function is still its main problem. In this paper  an improved particle filter  EM-PF algorithm is proposed which using the EM (Expectation-Maximization) algorithm to learn the dynamical models. The EM algorithm can explicitly learn the parameters of the dynamical models from training sequences. The advantage of using the EM algorithm in particle filter is that it is capable of improve tracking contour by having accurate model parameters. Though the experiment results  we show how our EM-PF can be applied to produces more robust and accurate extracting.   Detection and tracking of low contrast targets based on integertype lifting wavelet transform (EI CONFERENCE) 会议论文  OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China 作者:  Wang L.;  Wang L.;  Wang Y.;  Wang Y.;  Wang Y. 收藏  |  浏览/下载：18/0  |  提交时间：2013/03/25 This paper presents a method for detecting and tracking of low contrast targets. The new method uses an integer-type lifting wavelet transform and the proposed method doesn't extract patterns similar to a template  but finds parts having the same feature in the targets. We utilize one of integer-type lifting wavelet transforms that contains rounding-off arithmetic for mapping integers to integers. The lifting term contains parameters that are learned by using standard training images of targets. We assume that the targets include many high frequency components. In order to obtain the features of the targets  the lifting parameters are determined by a condition that high frequency components are vanished in wavelet transform. But the condition cannot be determined by the parameters wholly. So  we put an additional condition of minimizing the squared sum of the lifting parameters. The advantage of using integer-type wavelet transform is simple and robust to noise. Simulation illustrated the approach can detect and track the moving targets in dim background. We would test our algorithm in the TV tracking system.