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20212024
most citedDual-Branch Subpixel-Guided Network for Hyperspectral Image Classification

56 citations · 114 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024★ 23 cited

Multisource Collaborative Domain Generalization for Cross-Scene Remote Sensing Image Classification

Zhu Han, Ce Zhang, Lianru Gao +4

Cross-scene image classification aims to transfer prior knowledge of ground materials to annotate regions with different distributions and reduce hand-crafted cost in the field of…

eess.IV2024★ 56 cited

Dual-Branch Subpixel-Guided Network for Hyperspectral Image Classification

Zhu Han, Jin Yang, Lianru Gao +3

Deep learning (DL) has been widely applied into hyperspectral image (HSI) classification owing to its promising feature learning and representation capabilities. However, limited b…

cs.LG2022

Mixture GAN For Modulation Classification Resiliency Against Adversarial Attacks

Eyad Shtaiwi, Ahmed El Ouadrhiri, Majid Moradikia +3

Automatic modulation classification (AMC) using the Deep Neural Network (DNN) approach outperforms the traditional classification techniques, even in the presence of challenging wi…

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.LG2022

An Adaptive Device-Edge Co-Inference Framework Based on Soft Actor-Critic

Tao Niu, Yinglei Teng, Zhu Han +1

Recently, the applications of deep neural network (DNN) have been very prominent in many fields such as computer vision (CV) and natural language processing (NLP) due to its superi…

cs.CV2021★ 35 cited

SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers

Danfeng Hong, Zhu Han, Jing Yao +4

Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepanci…