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 ...

🔥YOLOv5作为单阶段目标检测算法的代表，以其高效性和准确性受到广泛关注。原始YOLOv5模型采用Backbone-Neck-Head的经典架构 ...

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 ...

Spending hours manually creating address objects on your Palo Alto Networks firewall? There’s a smarter, faster way! This guide will show you how to leverage the Pan-OS REST API and Python to automate ...

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 ...