Abstract: This paper presents a robust approach for object detection in aerial imagery using the YOLOv5 model. We focus on identifying critical objects such as ambulances, car crashes, police vehicles ...

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 ...

What if you could teach a computer to recognize a zebra without ever showing it one? Imagine a world where object detection isn’t bound by the limits of endless training data or high-powered hardware.

Introduction: Accurate vehicle analysis from aerial imagery has become increasingly vital for emerging technologies and public service applications such as intelligent traffic management, urban ...

Small object detection is a critical task in applications like autonomous driving and ship black smoke detection. While Deformable DETR has advanced small object detection, it faces limitations due to ...

Students call it hypocritical. A senior at Northeastern University demanded her tuition back. But instructors say generative A.I. tools make them better at their jobs. By Kashmir Hill In February, ...

This project implements real-time object detection using OpenCV and a pre-trained SSD MobileNet V3 model. The application can identify and label various objects from a webcam feed or uploaded images ...

Abstract: This paper describes an enhanced approach to perform object detection and tracking for the use of autonomous driving systems by using YOLOv5 model for the detection process, and Kalman ...