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 ...

Imagine a vehicle cruising at 54 kilometres per hour, roughly the speed of an object moving 0.5 metres per frame at 30 frames per second (0.5×30×3.6=54 km/hr). Mounted on the vehicle’s roof is a ...

This research investigates deep learning-based approach for defect detection in the steel production using Severstal steel dataset. The developed system integrates DenseNet121 for classification and ...

Hi everyone and @glenn-jocher. I am a beginner at using YOLOv5. My task is to detect objects from 4 classes of garbage (recyclable, harmful, kitchen, and other), which include various specific items ...

Abstract: This study tackles the intrinsic difficulties that come with fighting fire and addresses the urgent need to improve fire detection techniques. This study thoroughly assesses well-known ...

The food we eat is receiving a lot of attention due to the fast development of technology. Skilled labor is one of the most expensive components in the agricultural business. The industry is leaning ...

The detection of smoking behavior is an emerging field faced with challenges in identifying small, frequently occluded objects like cigarette butts using existing deep learning technologies. Such ...