Abstract: In biomedical image analysis, developing architectures that effectively capture long-range dependencies is crucial. Traditional Convolutional Neural Networks (CNNs) are constrained by their ...

Abstract: To address the shortcomings of traditional deep learning applications for multi-label satellite image classification, this work shifts focus toward lightweight Vision Transformers (ViTs) ...

First 4D Radar Automatic Labelling tools using Segment Anything (SA) drivable area segmentation on camera using Deep Learning for Autonomous Vehicle. KAIST-Radar (K-Radar) (provided by 'AVELab') is a ...

Introduction: Recently, the integration of deep learning techniques and computational materials science has catalyzed significant advances in the microstructural analysis of materials, particularly ...