activity
20162021
most citedDeep learning in remote sensing: a review

3.2k citations · 4.7k across the 23 of their papers we have counts for

collaborators
Showing 2021Show all

11 papers · 1 filter

eess.IV2021★ 1 cited

Binary Change Guided Hyperspectral Multiclass Change Detection

Meiqi Hu, Chen Wu, Bo Du +1

Characterized by tremendous spectral information, hyperspectral image is able to detect subtle changes and discriminate various change classes for change detection. The recent rese…

eess.IV2021★ 26 cited

Hidden Path Selection Network for Semantic Segmentation of Remote Sensing Images

Kunping Yang, Xin-Yi Tong, Gui-Song Xia +2

Targeting at depicting land covers with pixel-wise semantic categories, semantic segmentation in remote sensing images needs to portray diverse distributions over vast geographical…

cs.CV2021★ 24 cited

Self-Ensembling GAN for Cross-Domain Semantic Segmentation

Yonghao Xu, Fengxiang He, Bo Du +2

Deep neural networks (DNNs) have greatly contributed to the performance gains in semantic segmentation. Nevertheless, training DNNs generally requires large amounts of pixel-level…

cs.CV2021

LUAI Challenge 2021 on Learning to Understand Aerial Images

Gui-Song Xia, Jian Ding, Ming Qian +33

This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in a…

eess.IV2021★ 65 cited

Coupling Model-Driven and Data-Driven Methods for Remote Sensing Image Restoration and Fusion

Huanfeng Shen, Menghui Jiang, Jie Li +3

In the fields of image restoration and image fusion, model-driven methods and data-driven methods are the two representative frameworks. However, both approaches have their respect…

cs.CV2021

Change is Everywhere: Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery

Zhuo Zheng, Ailong Ma, Liangpei Zhang +1

For high spatial resolution (HSR) remote sensing images, bitemporal supervised learning always dominates change detection using many pairwise labeled bitemporal images. However, it…