Researchers propose a Vision Transformer approach that detects FFF surface defects in real time with on-demand explainability ...

In the last decade, convolutional neural networks (CNNs) have been the go-to architecture in computer vision, owing to their powerful capability in learning representations from images/videos.

A new study reports a ViT-YOLOv8 framework for smoke and fire detection, achieving 98.5% precision and improving early ...

Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications ...