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 ...
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 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 ...
Tracking is one of the most important components in object detection when it comes to real-world applications. Applications like real-time surveillance and autonomous driving systems cannot reach ...
Object detection is one of the most important challenges in computer vision. Deep learning-based solutions can solve it very effectively. To solve any problem using deep learning, first, we need to ...
Small object detection refers to the task of identifying and localizing objects that are relatively small in size within digital images. These objects typically have limited spatial extent and low ...
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