activity
20202022
most citedMore Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

1.4k citations · 1.8k across the 5 of their papers we have counts for

collaborators

8 papers

cs.CV2022

Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review

Minghua Wang, Danfeng Hong, Zhu Han +5

Owing to the rapid development of sensor technology, hyperspectral (HS) remote sensing (RS) imaging has provided a significant amount of spatial and spectral information for the ob…

cs.CV20222 cited

Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review

Jiaxin Li, Danfeng Hong, Lianru Gao +4

With the extremely rapid advances in remote sensing (RS) technology, a great quantity of Earth observation (EO) data featuring considerable and complicated heterogeneity is readily…

cs.CV2021185 cited

An Attention-Fused Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Imagery

Xuan Yang, Shanshan Li, Zhengchao Chen +5

Semantic segmentation is an essential part of deep learning. In recent years, with the development of remote sensing big data, semantic segmentation has been increasingly used in r…

eess.IV2021

Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing

Danfeng Hong, Lianru Gao, Jing Yao +4

Over the past decades, enormous efforts have been made to improve the performance of linear or nonlinear mixing models for hyperspectral unmixing, yet their ability to simultaneous…

cs.CV2021

FCCDN: Feature Constraint Network for VHR Image Change Detection

Pan Chen, Danfeng Hong, Zhengchao Chen +3

Change detection is the process of identifying pixelwise differences in bitemporal co-registered images. It is of great significance to Earth observations. Recently, with the emerg…

cs.CV2020

SLCRF: Subspace Learning with Conditional Random Field for Hyperspectral Image Classification

Yun Cao, Jie Mei, Yuebin Wang +5

Subspace learning (SL) plays an important role in hyperspectral image (HSI) classification, since it can provide an effective solution to reduce the redundant information in the im…