The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...

How does the brain manage to catch the drift of a mumbled sentence or a flat, robotic voice? A new study led by researchers at Reichman University's Baruch Ivcher School of Psychology and the Dina ...

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 ...

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

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 ...

School of Electronics Engineering (SENSE), Vellore Institute of Technology, Chennai, India Introduction: In recent years, Deep Learning (DL) architectures such as Convolutional Neural Network (CNN) ...

Under the background of the new distribution network, the power fluctuation on the line is increasing, which leads to more uncertainties in the predicted line loss ...

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...

What is CNN in Deep Learning? In this video, we understand what is CNN in Deep Learning and why do we need it. CNN (or Convolutional Neural Network) is the building block of all Computer Vision ...