The idea of these so-called perception-driven systems is to interpret raw sensor data and convert it into actionable understanding. So, they capture the images as traditional machine vision would, but ...

The ability of computers to learn on their own by using data is known as machine learning. It is closely related to artificial intelligence ...

Abstract: This study develops a scalable, effective, and user-friendly solution to tackle the problem of real-time object detection in photos. The suggested approach ...

Abstract: The increasing number of Near-Earth Objects (NEOs) has become a global concern due to the possibility of these objects colliding with Earth and causing serious damage. Traditionally, the ...

Amirali Aghazadeh receives funding from Georgia Tech. When NASA scientists opened the sample return canister from the OSIRIS-REx asteroid sample mission in late 2023, they found something astonishing.

This repository is the official Pytorch implementation for the paper Rethinking Multi-modal Object Detection from the Perspective of Mono-Modality Feature Learning. If you have any questions, please ...

Betting companies train machine learning programs to monitor players’ behaviour. AI technologies seem to have been integrated into every corner of our lives. Most businesses have jumped on the ...

Department of Electronics Communication Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai, India Introduction: Early and accurate detection of crop stress is vital for ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...