This paper presents and explores a robust deep learning framework for auscultation
analysis. This aims to classify anomalies in respiratory cycles and detect diseases, from …

This paper provides an analysis of state-of-the-art activation functions with respect to
supervised classification of deep neural network. These activation functions comprise of …

This article proposes an encoder-decoder network model for Acoustic Scene Classification
(ASC), the task of identifying the scene of an audio recording from its acoustic signature. We …

In this paper, we propose lightweight deep neural networks for Acoustic Scene Classification
(ASC) and a visualization method for presenting a sound scene context. To this end, we first …

In this work, we propose an approach that features deep feature embedding learning and
hierarchical classification with triplet loss function for Acoustic Scene Classification (ASC). In …

In this paper, we present a comprehensive analysis of Acoustic Scene Classification (ASC),
the task of identifying the scene of an audio recording from its acoustic signature. In …

In this paper, we present deep learning frameworks for audio-visual scene classification
(SC) and indicate how individual visual, audio features as well as their combination affect …

In this paper, we present a robust and low complexity model for Acoustic Scene
Classification (ASC), the task of identifying the scene of an audio recording. We firstly …

As speech recognition technologies have garnered increasing attention recently, the
possibility of integrating related technologies into the field of underwater acoustic target …

In this paper, we present the task of audio-visual scene classification (SC) where input
videos are classified into one of five real-life crowded scenes:'Riot','Noise-Street','Firework …