The CNN first extracts features from the image using a series of convolutional and pooling layers and then uses these features to make predictions about the presence of different objects.

Real-time object detection, which uses neural networks and deep learning to rapidly identify and tag objects of interest in a video feed, is a handy feature with great hacker potential. Happily, it… ...

Fig. 1: DETR transformer model compares its prediction with the ground truth. When there is no match, it would yield a “no object.” A match would validate an object. Source: “End-to-End Object ...