A clean, modular, real-time object detection pipeline built on YOLOv5 + PyTorch + OpenCV. It shows FPS, counts detected objects per frame, renders boxes, and (optionally) saves the video. torch==2.7.1 ...

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 ...

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

Maritime mobile edge computing (MMEC) technology facilitates the deployment of computationally intensive object detection tasks on Maritime Internet of Things (MIoT) devices with limited computing ...

I am working on an overhead object detection project using images with a resolution of 1280x1024. The objects are generally small (e.g., cars and people). The inference will be performed on the DPU.

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, ...

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 ...

Abstract: This paper describes the use of YOLOv5 transfer learning from the COCO dataset to train and deploy a custom model to detect select pantry objects in various lighting and orientations using ...