Object detection and recognition are an integral part of computer vision systems. In computer vision, the work begins with a breakdown of the scene into components that a computer can see and analyse.

Computer vision analysis has reached the point where it can identify not only a utility knife-type object, but also the exact circumstance under which it becomes dangerous to an employee.

Faster R-CNN, introduced in 2016, solves the final piece of the object-detection puzzle by integrating the region extraction mechanism into the object detection network.

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 ...

Called Faster Objects, More Objects (FOMO), the new deep learning architecture can unlock new computer vision applications. Most object-detection deep learning models have memory and computation ...

So, computer vision in smart transportation can resolve this through object detection and name recognition for such vehicles. The machine learning algorithms can identify the vehicle and its ...

Just making a small tweak to algorithms typically used to enhance images could dramatically boost computer vision recognition capabilities in applications ranging from self-driving cars to cybernetic ...