Adaptive method helps light-based quantum processors act more like neural networks

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...
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 ...
Cybernews

Humanoids might know how you feel and be 95% correct, AI research shows

Researchers have developed an artificial intelligence (AI) system that allows robots to distinguish between human emotions ...
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

On-Sensor Convolutional Neural Networks with Early-Exits

Abstract: Tiny Machine Learning (TinyML) is a novel research field aiming at integrating Machine Learning (ML) within embedded devices with limited memory, computation, and energy. Recently, a new ...
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 ...
IEEE

Speech Emotion Recognition using Branched-based Convolutional Neural Network Technique

Abstract: Speech Emotion Recognition is a significant pattern recognition of human speech using feature extraction for communication media. This paper aims to recognize speech emotion through the CNN ...