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 ...

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 ...

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.

Tea leaf diseases are significant causes of reduced quality and yield in tea production. In the Yunnan region, where the climate is suitable for tea cultivation, tea leaf diseases are small, scattered ...

Abstract: Detecting objects using deep learning technology has the advantage of getting good accuracy. The accuracy obtained depends on the processing time of using ...

New Caledonian crows may find tool use fun, according to a new study. This is an Inside Science story. (Inside Science) -- Getting food is nice. But scoring that food through clever tool use is even ...