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20182026
most citedMore Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

1.4k citations · 3.3k across the 24 of their papers we have counts for

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30 papers · 1 filter

cs.CV2026

DisasterTD: Disaster Toponym Disambiguation Using Multimodal LLMs and Cross-View Geolocalization

Wenping Yin, Ziqi Liu, Naixia Mou +3

Social media imagery (SMI) provides timely and fine-grained ground perspectives that are valuable for situational awareness and emergency response. Unlike satellite or aerial image…

cs.CV2024

Superpixelwise Low-rank Approximation based Partial Label Learning for Hyperspectral Image Classification

Shujun Yang, Yu Zhang, Yao Ding +1

Insufficient prior knowledge of a captured hyperspectral image (HSI) scene may lead the experts or the automatic labeling systems to offer incorrect labels or ambiguous labels (i.e…

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.CV2023

Spatial Gated Multi-Layer Perceptron for Land Use and Land Cover Mapping

Ali Jamali, Swalpa Kumar Roy, Danfeng Hong +2

Convolutional Neural Networks (CNNs) are models that are utilized extensively for the hierarchical extraction of features. Vision transformers (ViTs), through the use of a self-att…