output
20162024
most citedDeep learning in remote sensing: a review

3.2k citations

35 papers

cs.CV202474 cited

C2F-SemiCD: A Coarse-to-Fine Semi-Supervised Change Detection Method Based on Consistency Regularization in High-Resolution Remote Sensing Images

Chengxi Han, Chen Wu, Meiqi Hu +2

A high-precision feature extraction model is crucial for change detection (CD). In the past, many deep learning-based supervised CD methods learned to recognize change feature patt…

astro-ph.EP20245 cited

Dynamical Model of Rotation and Orbital Coupling for Deimos

Kai Huang, Lijun Zhang, Yongzhang Yang +2

This paper introduces a novel dynamical model, building upon the existing dynamical model for Deimos in the current numerical ephemerides, which only encompasses the simple librati…

cs.CV2024164 cited

Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery

Chengxi Han, Chen Wu, Haonan Guo +3

The rapid advancement of automated artificial intelligence algorithms and remote sensing instruments has benefited change detection (CD) tasks. However, there is still a lot of spa…

cs.CV2024248 cited

HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images

Chengxi Han, Chen Wu, Haonan Guo +2

Benefiting from the developments in deep learning technology, deep-learning-based algorithms employing automatic feature extraction have achieved remarkable performance on the chan…

cs.CV202448 cited

Deep Blind Super-Resolution for Satellite Video

Yi Xiao, Qiangqiang Yuan, Qiang Zhang +1

Recent efforts have witnessed remarkable progress in Satellite Video Super-Resolution (SVSR). However, most SVSR methods usually assume the degradation is fixed and known, e.g., bi…

cs.CV202394 cited

DCN-T: Dual Context Network with Transformer for Hyperspectral Image Classification

Di Wang, Jing Zhang, Bo Du +2

Hyperspectral image (HSI) classification is challenging due to spatial variability caused by complex imaging conditions. Prior methods suffer from limited representation ability, a…