Some computers are easy to spot. Artificial, human-built computers like those found in smartphones and laptops are abstract ...

As we approach the AI Impact Summit 2026, global AI exosystems are undergoing a brutal yet necessary recalibration. Those calibrations are driven by t.

Abstract: Vision GNNs (ViGs) divide an image into multiple patches, treating these image patches as graph nodes. The image is represented by extracting explicit features from these patches as node ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

This research addresses the challenge of monitoring railway driver drowsiness using a real-time, vision-based system powered by convolutional neural networks, specifically the YOLOv8 architecture ...

The prediction of the properties of crystal materials has always been a core issue in materials science and solid-state physics. With the rapid development of computer simulation techniques and ...

Brain-computer interfaces (BCIs) are advanced and innovative systems that enable direct communication between humans and external devices by utilizing data encoded in the brain activity (Shi et al., ...

Abstract: Vision Graph Neural Network (ViG) is the first graph neural network model capable of directly processing image data. The community primarily focuses on the model structures to improve ViG's ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

Our system implements a sophisticated multi-stage pipeline that combines traditional computer vision with cutting-edge deep learning approaches to achieve state-of-the-art receipt information ...