An overview of deep learning architectures that help computers detect objects, a key technology used in self-driving cars and healthcare.

Today, many applications use object-detection networks as one of their main components. It’s in your phone, computer, car, camera, and more.

Deep learning hasn't (yet) rendered classical computer vision obsolete. Why some challenges are still best solved with traditional algorithms.

YOLO (You Only Look Once): A real-time object detection algorithm known for its rapid processing speed and high detection accuracy, particularly useful in industrial inspection applications.

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.

Siwei Lyu is a UB faculty expert on digital media forensics, deepfakes, computer vision, machine learning and art authentication.

Since deep learning models typically rely on large volumes of annotated data to automatically learn features for subsequent detection tasks, the CV and MI domains often suffer from the “ small ...

AI vision is not only about automation. A well-developed computer vision system adjusted to specific business requirements can solve different problems industrial companies may face.

Future integration of the deep learning algorithm into standard system software would allow factory engineers to train networks that could then be run locally for inspection. There are many more ...