YOLO

YOLO11 on Raspberry Pi: Optimizing Object Detection for Edge Devices

Imagine you have multiple warehouses in different places where you don’t have time to monitor everything at a time, and you can’t afford a lot of computes due to their

Computer Vision, Edge Devices, Object Detection, Object Tracking, Raspberry Pi, YOLO

Fine-Tuning YOLOv12: Comparison with YOLOv11 & Darknet-Based YOLOv7

Object detection has undergone tremendous advancements, with models like YOLOv12, YOLOv11, and Darknet-Based YOLOv7 leading the way in real-time detection. While these models perform exceptionally well on general object detection

Computer Vision, Object Detection, YOLO

YOLOv12: Object Detection with Attention

Real-time object detection has become essential for many practical applications, and the YOLO (You Only Look Once) series by Ultralytics has always been a state-of-the-art model series, providing a robust

Computer Vision, Object Detection, YOLO

YOLO11: Redefining Real-Time Object Detection

YOLO11 is here! Continuing the legacy of the YOLO series, YOLO11 sets new standards in speed and efficiency. With enhanced architecture and multi-task capabilities, it outperforms previous models, making it

Computer Vision, Image Classification, Image Segmentation, Object Detection, Pose Estimation, YOLO

Fine-Tuning YOLOv10 Models on Custom Dataset for Kidney Stone Detection

This research article explains a data-centric fine-tuning approach using YOLOv10 models for kidney stone detection.

Computer Vision, Deep Learning, Medical Imaging, Object Detection, YOLO

YOLOv10: The Dual-Head OG of YOLO Series

YOLOv10 introduces a dual-head architecture for NMS-free training and efficiency-accuracy driven model design. It combines one-to-one and one-to-many label assignments to improve performance without extra computation. YOLOv10 uses lightweight classification

Computer Vision, Deep Learning, Object Detection, YOLO