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20202026
most citedMore Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

1.4k citations · 1.6k across the 14 of their papers we have counts for

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11 papers · 1 filter

cs.CV2026

SoDa2: Single-Stage Open-Set Domain Adaptation via Decoupled Alignment for Cross-Scene Hyperspectral Image Classification

Yiwen Liu, Minghua Wang, Jing Yao +2

Cross-scene hyperspectral image (HSI) classification stands as a fundamental research topic in remote sensing, with extensive applications spanning various fields. Owing to the inc…

cs.CV202438 cited

SpectralMamba: Efficient Mamba for Hyperspectral Image Classification

Jing Yao, Danfeng Hong, Chenyu Li +1

Recurrent neural networks and Transformers have recently dominated most applications in hyperspectral (HS) imaging, owing to their capability to capture long-range dependencies fro…

cs.CV2023

SpectralGPT: Spectral Remote Sensing Foundation Model

Danfeng Hong, Bing Zhang, Xuyang Li +11

The foundation model has recently garnered significant attention due to its potential to revolutionize the field of visual representation learning in a self-supervised manner. Whil…

cs.CV20238 cited

Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networks

Danfeng Hong, Bing Zhang, Hao Li +7

Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-modality-dominated remote sensing (RS) applications, especially with an emphasis on indivi…

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…