Meta’s Brain2Qwerty v2 turns thoughts into text, and it doesn’t need brain implants

Meta has unveiled Brain2Qwerty v2, an AI system that converts brain activity into text without surgery, bringing assistive communication a step closer to reality.
GitHub

adaptive_hyper-graph_convolution_network_for_skeleton-based_human_action_recogni.md

description [ICCV 2025][Video Understanding][Skeleton-based action recognition] This paper proposes Hyper-GCN, which replaces conventional binary graphs with an **adaptive non-uniform hypergraph** to ...
Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
IEEE

Graph Convolutional Network for Point Cloud Understanding Through Homogeneity Partitioning

Abstract: Effectively capturing complex point cloud information is essential for advanced functionalities in consumer electronics, such as augmented reality, virtual simulations, and 3D printing.
Scientific Research Publishing

Taye, M.M. (2023) Theoretical Understanding of Convolutional Neural Network: Concepts, Architectures, Applications, Future Directions. Computation, 11, Article 52.

ABSTRACT: In medical imaging, particularly for analyzing brain tumor MRIs, the expertise of skilled neurosurgeons or radiologists is often essential. However, many developing countries face a ...
IEEE

Understanding Convolutional Neural Networks From Excitations

Abstract: Saliency maps have proven to be a highly efficacious approach for explicating the decisions of convolutional neural networks (CNNs). However, extant methodologies predominantly rely on ...