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20182026
most citedGraph Convolutional Networks for Hyperspectral Image Classification

1.7k citations · 11.2k across the 45 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.CV2022★ 1.1k cited

UIU-Net: U-Net in U-Net for Infrared Small Object Detection

Xin Wu, Danfeng Hong, Jocelyn Chanussot

Learning-based infrared small object detection methods currently rely heavily on the classification backbone network. This tends to result in tiny object loss and feature distingui…

cs.CV2022★ 8 cited

Panchromatic and Multispectral Image Fusion via Alternating Reverse Filtering Network

Keyu Yan, Man Zhou, Jie Huang +4

Panchromatic (PAN) and multi-spectral (MS) image fusion, named Pan-sharpening, refers to super-resolve the low-resolution (LR) multi-spectral (MS) images in the spatial domain to g…

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…

eess.IV2022★ 8 cited

Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel Fusion

Danfeng Hong, Jing Yao, Deyu Meng +2

Enormous efforts have been recently made to super-resolve hyperspectral (HS) images with the aid of high spatial resolution multispectral (MS) images. Most prior works usually perf…

cs.CV2022★ 2 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.CV2022★ 511 cited

Multimodal Fusion Transformer for Remote Sensing Image Classification

Swalpa Kumar Roy, Ankur Deria, Danfeng Hong +3

Vision transformers (ViTs) have been trending in image classification tasks due to their promising performance when compared to convolutional neural networks (CNNs). As a result, m…