Monitoring forest health typically relies on remote sensing tools such as light detection and ranging (LiDAR), radar, and ...

Abstract: Remote sensing scene classification is a vital task in remote sensing image analysis with significant application potential. In recent years, convolutional neural network (CNN)-based methods ...

More information: Anwarul Islam Chowdhury et al, Mapping large European aspens (Populus tremula L.) using national aerial imagery and a U-Net convolutional neural network, Remote Sensing Applications: ...

Center for Neurology, The Thirteenth People’s Hospital of Chongqing, Chongqing, China The rapid growth of computational neuroscience and brain–computer interface (BCI) technologies require efficient, ...

has been cited by the following article: TITLE: Using Machine Learning Models to Predict Daily PM10 Concentration in the Wet Savanna of Lamto Station in Côte d’Ivoire ...

Abstract: Satellite image classification is a key task in remote sensing, where deep learning models are increasingly applied for their accuracy and automation capabilities. This study conducts a ...

Salient Object Detection in Optical Remote Sensing Images (ORSI-SOD) is vital for applications such as urban planning and disaster monitoring. Yet, existing deep models remain energy-intensive and ...

This repository documents my complete learning journey through the Coursera course Remote Sensing Image Acquisition, Analysis, and Applications. It is part of my broader PhD preparation plan in ...

ABSTRACT: This paper studies recent assistive technologies and AI sound detection systems that have been developed to support both the safety and communication of individuals who are deaf. It ...

Remote Desktop Protocol (RDP) allows you to access your computer over a network, but connecting from outside your local network (over the internet) introduces additional challenges. If you can connect ...