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20172023
most citedSpatial-Spectral Feature Extraction via Deep ConvLSTM Neural Networks for Hyperspectral Image Classification

218 citations · 974 across the 14 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

eess.IV2022★ 43 cited

Synthetic Aperture Radar Image Change Detection via Layer Attention-Based Noise-Tolerant Network

Desen Meng, Feng Gao, Junyu Dong +2

Recently, change detection methods for synthetic aperture radar (SAR) images based on convolutional neural networks (CNN) have gained increasing research attention. However, existi…

cs.CV2022★ 2 cited

Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review

Xin-Ru Feng, Heng-Chao Li, Rui Wang +3

Hyperspectral unmixing has been an important technique that estimates a set of endmembers and their corresponding abundances from a hyperspectral image (HSI). Nonnegative matrix fa…

cs.CV2022

Adaptive Cross-Attention-Driven Spatial-Spectral Graph Convolutional Network for Hyperspectral Image Classification

Jin-Yu Yang, Heng-Chao Li, Wen-Shuai Hu +2

Recently, graph convolutional networks (GCNs) have been developed to explore spatial relationship between pixels, achieving better classification performance of hyperspectral image…

cs.CV2022★ 149 cited

A3CLNN: Spatial, Spectral and Multiscale Attention ConvLSTM Neural Network for Multisource Remote Sensing Data Classification

Heng-Chao Li, Wen-Shuai Hu, Wei Li +3

The problem of effectively exploiting the information multiple data sources has become a relevant but challenging research topic in remote sensing. In this paper, we propose a new…

eess.IV2022★ 1 cited

Change Detection from Synthetic Aperture Radar Images via Dual Path Denoising Network

Junjie Wang, Feng Gao, Junyu Dong +2

Benefited from the rapid and sustainable development of synthetic aperture radar (SAR) sensors, change detection from SAR images has received increasing attentions over the past fe…

eess.IV2022★ 79 cited

SAR Image Change Detection Based on Multiscale Capsule Network

Yunhao Gao, Feng Gao, Junyu Dong +1

Traditional synthetic aperture radar image change detection methods based on convolutional neural networks (CNNs) face the challenges of speckle noise and deformation sensitivity.…