IEEE

A Novel Transformer-KAN Network Utilizes Multimodality Contrastive Learning and Mask Reconstruction for Remote Sensing Classification

Abstract: Contrastive learning is a promising paradigm in the multimodal few-shot domain, leveraging images captured from different sensors as diverse perspectives of the same ground objects. However, ...
IEEE

Federated Learning for Remote Sensing Image Classification Using Sparse Image Representations

Abstract: The increasing scale and complexity of remote sensing (RS) observations demand distributed processing to effectively manage the vast volumes of data generated. However, distributed ...
GitHub

SiamSeg: Self-Training with Contrastive Learning for Unsupervised Domain Adaptation Semantic Segmentation in Remote Sensing

Prediction results of our proposed method. Network Architectural and Cross-domain Image Different. torch=1.10.2,torchvision=0.11.3 and mmcv-full=1.5.0. Recommended use of conda virtual environments ...
Hosted on MSN

Park City Schools prepares to transition to remote learning

More coverage of Billings and Montana: <a href="https://ktvq.com">https://ktvq.com</a> Venezuela has a ton of oil. It also has something else America needs Newly ...
GitHub

InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object Recognition

InstructSAM is a training-free framework for Instruction-Oriented Object Counting, Detection, and Segmentation (InstructCDS). We construct EarthInstruct, an InstructCDS benchmark for remote sensing.