Morning Overview on MSN

Meta demonstrates AI that decodes thoughts from brain signals

Meta is testing artificial intelligence systems that can turn patterns of brain activity into text, effectively letting ...
IEEE

A Multi-Scale Feature Refinement and Dual-Attention Enhanced Dynamic Convolutional Network for Speech-Based Depression and ADHD Assessment

Abstract: In the area of affective computing, speech has been identified as a promising biomarker for assessing depression and attention deficit hyperactivity disorder (ADHD). These disorders manifest ...
IEEE

Fake Image Detection in Fake News Using Convolutional Neural Network (CNN)

Abstract: ’Fake news’ refers to false, inaccurate, or misleading information that spreads as real news. Fake news primarily aims to affect societies and individuals by spreading false or misleading ...
IEEE

Adaptive Convolution for CNN-Based Speech Enhancement Models

Abstract: Deep learning-based speech enhancement methods have significantly improved speech quality and intelligibility. Convolutional neural networks (CNNs) have been proven to be essential ...
IEEE

A Survey on Convolution Neural Networks

Abstract: Major tools to implement any Artificial Intelligence and Machine Learning systems are Symbolic AI and Artificial Neural Network (ANN) AI. ANN has made a dramatic improvement in the versatile ...
Scientific Research Publishing

Han, Y., Kim, J., & Lee, K. (2017). Deep Convolutional Neural Networks for Predominant Instrument Recognition in Polyphonic Music. IEEE/ACM Transactions on Audio, Speech, and ...

ABSTRACT: The study adapts several machine-learning and deep-learning architectures to recognize 63 traditional instruments in weakly labelled, polyphonic audio synthesized from the proprietary Sound ...