IEEE

Multiscale Semantic Segmentation of Remote Sensing Images Based on Edge Optimization

Abstract: Semantic segmentation of remote sensing images is crucial for disaster monitoring, urban planning, and land use. Due to scene complexity and multiscale features of targets, semantic ...
TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...
IEEE

DC-GCN: A Lightweight Graph Convolutional Network Integrating Local and Global Context for Semantic Segmentation

Abstract: Graph convolutional networks (GCNs) have demonstrated remarkable performance in hyperspectral image classification and remote sensing scene recognition. However, their application to ...
The New York Times

‘Unrestrained’ Chinese Cyberattackers May Have Stolen Data From Almost Every American

Information collected during the yearslong Salt Typhoon attack could allow Beijing’s intelligence services to track targets from the United States and dozens of other countries. By Adam Goldman ...
Frontiers

DynTransNet: Dynamic Transformer Network with multi-scale attention for liver cancer segmentation

Introduction: Hepatocellular carcinoma (HCC), a predominant subtype of liver cancer, remains Q7 a major contributor to global cancer mortality. Accurate delineation of liver tumors in CT and MRI scans ...
Frontiers

A 3D Fully Convolutional Neural Network With Top-Down Attention-Guided Refinement for Accurate and Robust Automatic Segmentation of Amygdala and Its Subnuclei

Recent advances in deep learning have improved the segmentation accuracy of subcortical brain structures, which would be useful in neuroimaging studies of many neurological disorders. However, most ...