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 ...

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 ...

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 ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

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 ...

Abstract: Object detection underwater is one of the most important tasks in various applications: marine biology, environ- mental monitoring, and underwater exploration. In this paper, we discuss a ...

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 ...