IEEE

Enhancing ResNet50 with Depth-wise Separable Convolution Squeeze-and-Excitation and Channel Squeeze-and-Excitation Modules for Accurate Remote Sensing Image Scene Classification

Abstract: Remote sensing image scene classification is crucial for urban planning and disaster monitoring. Existing methods often struggle with extracting local texture and global semantic features ...
IEEE

A Lightweight Semantic Segmentation Network Based on Self-Attention Mechanism and State Space Model for Efficient Urban Scene Segmentation

Abstract: In the semantic segmentation of remote sensing images, methods based on convolutional neural networks (CNNs) and Transformers have been extensively studied. Nevertheless, CNN struggles to ...