In the preceding article, YOLO Loss Functions Part 1, we focused exclusively on SIoU and Focal Loss as the primary loss functions used in the YOLO series of models. In this article, we will dive ...
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YOLOv8 Object Tracking and Counting with OpenCV
In the realm of computer vision, YOLOv8 object tracking is revolutionizing the way we approach real-time tracking and analysis of moving objects. This article takes a close look at the fascinating ...
Stereo Vision in ADAS: Pioneering Depth Perception Beyond LiDAR
Explore the dynamic world of ADAS (Advanced Driver Assistance Systems) and the innovative field of stereo vision. In this article, we'll explore how ADAS stereo vision in cars is changing the game, ...
YOLO Loss Function Part 1: SIoU and Focal Loss
The YOLO (You Only Look Once) series of models, renowned for its real-time object detection capabilities, owes much of its effectiveness to its specialized loss functions. In this article, we delve ...
Moving Object Detection with OpenCV using Contour Detection and Background Subtraction
Moving object detection is used extensively for applications ranging from security surveillance to traffic monitoring. It is a crucial challenge in the ever-evolving field of computer vision. The ...
Integrating ADAS with Keypoint Feature Pyramid Network for 3D LiDAR Object Detection
3D LiDAR object detection is a process that assists with identifying and localizing objects of interest in a 3-dimensional space. In autonomous systems and advanced spatial analysis, the evolution of ...
