Intersection over Union
In the constantly evolving field of computer vision, understanding the precise structure and pose of objects is essential. Whether it’s detecting a specific object in a cluttered scene or analyzing
Weighted box fusion: The post-processing step is a trivial yet important component in object detection. In this article, we will demonstrate the significance of Weighted Boxes Fusion (WBF) as opposed
Intersection Over Union (IoU) quantifies degree of overlap between two boxes. In Deep Learning, it is a model evaulation helper metric.
Non Maximum Suppression (NMS) is a technique used in numerous computer vision tasks. It is a class of algorithms to select one entity (e.g., bounding boxes) out of many overlapping
