1.9k citations · 6.2k across the 72 of their papers we have counts for
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Masking Hyperspectral Imaging Data with Pretrained Models
Elias Arbash, Andréa de Lima Ribeiro, Sam Thiele +5
The presence of undesired background areas associated with potential noise and unknown spectral characteristics degrades the performance of hyperspectral data processing. Masking o…
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…
RSAdapter: Adapting Multimodal Models for Remote Sensing Visual Question Answering
Yuduo Wang, Pedram Ghamisi
In recent years, with the rapid advancement of transformer models, transformer-based multimodal architectures have found wide application in various downstream tasks, including but…
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…
Universal Adversarial Defense in Remote Sensing Based on Pre-trained Denoising Diffusion Models
Weikang Yu, Yonghao Xu, Pedram Ghamisi
Deep neural networks (DNNs) have risen to prominence as key solutions in numerous AI applications for earth observation (AI4EO). However, their susceptibility to adversarial exampl…
Neighborhood Attention Makes the Encoder of ResUNet Stronger for Accurate Road Extraction
Ali Jamali, Swalpa Kumar Roy, Jonathan Li +1
In the domain of remote sensing image interpretation, road extraction from high-resolution aerial imagery has already been a hot research topic. Although deep CNNs have presented e…
Tinto: Multisensor Benchmark for 3D Hyperspectral Point Cloud Segmentation in the Geosciences
Ahmed J. Afifi, Samuel T. Thiele, Aldino Rizaldy +6
The increasing use of deep learning techniques has reduced interpretation time and, ideally, reduced interpreter bias by automatically deriving geological maps from digital outcrop…
Dsfer-Net: A Deep Supervision and Feature Retrieval Network for Bitemporal Change Detection Using Modern Hopfield Networks
Shizhen Chang, Michael Kopp, Pedram Ghamisi +1
Change detection, an essential application for high-resolution remote sensing images, aims to monitor and analyze changes in the land surface over time. Due to the rapid increase i…
Changes to Captions: An Attentive Network for Remote Sensing Change Captioning
Shizhen Chang, Pedram Ghamisi
In recent years, advanced research has focused on the direct learning and analysis of remote sensing images using natural language processing (NLP) techniques. The ability to accur…