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TCDM: Effective Large-Factor Image Super-Resolution via Texture Consistency Diffusion 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 卷号: 62, 页码: 13
作者:  Zhang, Yan;  Liu, Hanqi;  Li, Zhenghao;  Gao, Xinbo;  Shi, Guangyao;  Jiang, Jianan
收藏  |  浏览/下载：5/0  |  提交时间：2024/04/07
Remote sensing  Image reconstruction  Task analysis  Superresolution  Transformers  Faces  Image restoration  Diffusion models (DMs)  large-factor image super-resolution (SR)  remote sensing images  texture consistency  
A Novel Adaptive Edge Aggregation and Multiscale Feature Interaction Detector for Object Detection in Remote Sensing Images 期刊论文
REMOTE SENSING, 2023, 卷号: 15, 期号: 21, 页码: 21
作者:  Huang, Wei;  Zhao, Yuhao;  Sun, Le;  Gao, Lu;  Chen, Yuwen
收藏  |  浏览/下载：19/0  |  提交时间：2023/12/25
edge enhancement  local and nonlocal contexts  cross-attention  level-by-level feature fusion  object detection  remote sensing images  
CRNet: Channel-Enhanced Remodeling-Based Network for Salient Object Detection in Optical Remote Sensing Images 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 卷号: 61, 页码: 14
作者:  Sun, Le;  Wang, Qing;  Chen, Yuwen;  Zheng, Yuhui;  Wu, Zebin;  Fu, Liyong;  Jeon, Byeungwoo
收藏  |  浏览/下载：13/0  |  提交时间：2023/12/25
Channel enhance module (CEM)  optical remote sensing images (RSIS)  redefined feature module (RFM)  salient object detection (SOD)  
Remotely Sensed Mid-Channel Bar Dynamics in Downstream of the Three Gorges Dam, China 期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 3, 页码: 21
作者:  Wen, Zhaofei;  Yang, Hong;  Zhang, Ce;  Shao, Guofan;  Wu, Shengjun
收藏  |  浏览/下载：112/0  |  提交时间：2020/08/24
Landsat images  remote sensing  time series analysis  Three Gorges Dam  Dam effects  Geomorphic dynamics  River bar  River island  
A novel remote sensing image retrieval method based on visual salient point features 期刊论文
SENSOR REVIEW, 2014, 卷号: 34, 期号: 4, 页码: 349-359
作者:  Wang, Xing;  Shao, Zhenfeng;  Zhou, Xiran;  Liu, Jun
收藏  |  浏览/下载：52/0  |  提交时间：2018/03/15
Image retrieval  Image key points  Remote sensing images  Visual attention models