This module is integrated into the YOLOv11 object detection framework, thereby enhancing both the accuracy and robustness of the detection system. The diffusion behavior of leaking gas exhibits unique ...

YOLO is one of the most popular edge AI computer vision models that detects multiple objects and works out of the box for the objects for which it has been trained on. But adding another object would ...

TL;DR Key Takeaways : The Raspberry Pi AI HAT, combined with YOLO models, enables real-time object detection, counting, and positional tracking for applications like security and automation.

This paper presents a comprehensive approach to face detection utilizing the YOLOv8 model, specifically trained on a diverse dataset consisting of images from four individuals. The trained model is ...

Textile quality assurance during processing is accomplished through fabric defect detection which is among the most important processes. The conventional manual inspection techniques are time ...

Object Detection is the task of finding objects within an image or video. The task is not only to find the object but to label it and create a bounding box around the object. In autonomous navigation ...

The YOLOv7 model has the highest mAP and FPS rate in the range of 5 to 160 FPS. Conclusion YOLO or You Only Look Once is the state of the art object detection model in modern computer vision. The YOLO ...

This engine is not only data and hardware aware but also considers other components in the inference stack, such as compilers and quantization. YOLO-NAS delivers state-of-the-art performance with ...

In their empirical study, the team compared RT-DETR with baseline real-time and end-to-end object detectors such as YOLO, PPYOLOE, Efficient-DETR, etc. In the experiments, RT-DETR-L achieved 53.0 ...