Object detection in computer vision encompasses the automatic identification and localisation of objects within images or video streams. Early approaches relied on handcrafted features and shallow ...

IDDEA illustrates the shift from generic category recognition to variant-level identification, enabling defense AI systems to ...

Unsafe behaviors of miners are a primary cause of coal mine accidents, and intelligent video monitoring is an important means of preventing such accidents. To improve unsafe-behavior recognition in ...

A new ensemble deep learning framework called EnPreNiNet, paired with a night image enhancement technique, achieved a reported mean Average Precision of 76.3 percent for multi-object detection in ...

A new YOLOv8-based algorithm called DARF improves visible-infrared object detection by enhancing shallow features and ...

Ultralytics is the company behind YOLO, an open-source computer vision model used for tasks including detection, segmentation, classification, and pose estimation. The company also offers the ...

The object detection required for machine vision applications such as autonomous driving, smart manufacturing, and surveillance applications depends on AI modeling. The goal now is to improve the ...

Umashanker Bandari’s co-authored IEEE Xplore paper explores a context-aware deep learning framework for accurate, efficient, ...

Physical AI is taking artificial intelligence beyond software and into factories, hospitals and other real-world environments ...

Why counter drone drone and modern aerial threat need a AI brain to detect and neutralize them by using computer vision, mainly ...

Selecting the right edge device for real-time AI-powered vision is a critical decision that can impact the performance, usability, and versatility of your applications. This comparison between the ...