YOLO
Imagine you have multiple warehouses in different places where you don 8217 t have time to monitor everything at a time and you can 8217 t afford a lot of
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
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
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
This research article explains a data centric fine tuning approach using YOLOv10 models for kidney stone detection
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
