205 citations · 683 across the 16 of their papers we have counts for
7 papers · 1 filter
AI Security for Geoscience and Remote Sensing: Challenges and Future Trends
Yonghao Xu, Tao Bai, Weikang Yu +3
Recent advances in artificial intelligence (AI) have significantly intensified research in the geoscience and remote sensing (RS) field. AI algorithms, especially deep learning-bas…
Backdoor Attacks for Remote Sensing Data with Wavelet Transform
Nikolaus Dräger, Yonghao Xu, Pedram Ghamisi
Recent years have witnessed the great success of deep learning algorithms in the geoscience and remote sensing realm. Nevertheless, the security and robustness of deep learning mod…
The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection from Multi-Source Satellite Imagery
Omid Ghorbanzadeh, Yonghao Xu, Hengwei Zhao +12
The scientific outcomes of the 2022 Landslide4Sense (L4S) competition organized by the Institute of Advanced Research in Artificial Intelligence (IARAI) are presented here. The obj…
Txt2Img-MHN: Remote Sensing Image Generation from Text Using Modern Hopfield Networks
Yonghao Xu, Weikang Yu, Pedram Ghamisi +2
The synthesis of high-resolution remote sensing images based on text descriptions has great potential in many practical application scenarios. Although deep neural networks have ac…
Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection
Omid Ghorbanzadeh, Yonghao Xu, Pedram Ghamisi +2
This study introduces \textit{Landslide4Sense}, a reference benchmark for landslide detection from remote sensing. The repository features 3,799 image patches fusing optical layers…
Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark
Yonghao Xu, Pedram Ghamisi
Deep neural networks have achieved great success in many important remote sensing tasks. Nevertheless, their vulnerability to adversarial examples should not be neglected. In this…
Consistency-Regularized Region-Growing Network for Semantic Segmentation of Urban Scenes with Point-Level Annotations
Yonghao Xu, Pedram Ghamisi
Deep learning algorithms have obtained great success in semantic segmentation of very high-resolution (VHR) images. Nevertheless, training these models generally requires a large a…