activity
20172021
most citedDeep learning in remote sensing: a review

3.2k citations · 4.4k across the 17 of their papers we have counts for

collaborators

37 papers

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…

cs.CV2021191 cited

A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification

Qiqi Zhu, Weihuan Deng, Zhuo Zheng +5

Deep learning techniques have been widely applied to hyperspectral image (HSI) classification and have achieved great success. However, the deep neural network model has a large pa…

cs.CV2021

Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing

Danfeng Hong, Wei He, Naoto Yokoya +5

Hyperspectral imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS). In the past decade, enormous efforts have been made to proce…

eess.IV2021

Super-resolution-based Change Detection Network with Stacked Attention Module for Images with Different Resolutions

Mengxi Liu, Qian Shi, Andrea Marinoni +3

Change detection, which aims to distinguish surface changes based on bi-temporal images, plays a vital role in ecological protection and urban planning. Since high resolution (HR)…

eess.SP2021

Long time-series NDVI reconstruction in cloud-prone regions via spatio-temporal tensor completion

Dong Chu, Huanfeng Shen, Xiaobin Guan +4

The applications of Normalized Difference Vegetation Index (NDVI) time-series data are inevitably hampered by cloud-induced gaps and noise. Although numerous reconstruction methods…

eess.IV20202 cited

Spectral Response Function Guided Deep Optimization-driven Network for Spectral Super-resolution

Jiang He, Jie Li, Qiangqiang Yuan +2

Hyperspectral images are crucial for many research works. Spectral super-resolution (SSR) is a method used to obtain high spatial resolution (HR) hyperspectral images from HR multi…