205 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Austrian Research Institute for Artificial IntelligenceAT18 papers
- Helmholtz Institute Freiberg for Resource TechnologyDE10 papers
- Helmholtz-Zentrum Dresden-RossendorfDE10 papers
- TU WienAT5 papers
- Complexity and Topology in Quantum MatterDE3 papers
- University of TorontoCA3 papers
- University of WürzburgDE3 papers
- Wuhan UniversityCN3 papers
- Hunan UniversityCN2 papers
- Johannes Kepler University of LinzAT2 papers
- Peng Cheng LaboratoryCN2 papers
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingCN2 papers
11 papers · 1 filter
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…
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network
Mario Krenn, Lorenzo Buffoni, Bruno Coutinho +13
A tool that could suggest new personalized research directions and ideas by taking insights from the scientific literature could significantly accelerate the progress of science. A…
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…
Trackintel: An open-source Python library for human mobility analysis
Henry Martin, Ye Hong, Nina Wiedemann +2
Over the past decade, scientific studies have used the growing availability of large tracking datasets to enhance our understanding of human mobility behavior. However, so far data…
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…
What to Hide from Your Students: Attention-Guided Masked Image Modeling
Ioannis Kakogeorgiou, Spyros Gidaris, Bill Psomas +4
Transformers and masked language modeling are quickly being adopted and explored in computer vision as vision transformers and masked image modeling (MIM). In this work, we argue t…
Nonnegative-Constrained Joint Collaborative Representation with Union Dictionary for Hyperspectral Anomaly Detection
Shizhen Chang, Pedram Ghamisi
Recently, many collaborative representation-based (CR) algorithms have been proposed for hyperspectral anomaly detection. CR-based detectors approximate the image by a linear combi…
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…
Asymmetric Hash Code Learning for Remote Sensing Image Retrieval
Weiwei Song, Zhi Gao, Renwei Dian +3
Remote sensing image retrieval (RSIR), aiming at searching for a set of similar items to a given query image, is a very important task in remote sensing applications. Deep hashing…
NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote Sensing Imagery
Ming Lu, Leyuan Fang, Muxing Li +3
The use of deep learning for water extraction requires precise pixel-level labels. However, it is very difficult to label high-resolution remote sensing images at the pixel level.…