Forest ecosystems are of paramount importance to the sustainable existence of life on earth.
Unique natural and artificial phenomena pose severe threats to the perseverance of such …

Abstract The Human Activity Recognition (HAR) problem leverages pattern recognition to
classify physical human activities as they are captured by several sensor modalities. Remote …

Underwater target classification using passive sonar remains a critical issue due to the
changeable ocean environment. Convolutional neural networks (CNNs) have shown …

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 …

Cardiac auscultation is an essential point-of-care method used for the early diagnosis of
heart diseases. Automatic analysis of heart sounds for abnormality detection is faced with …

Music genre is one of the conventional ways to describe music content, and also is one of
the important labels of music information retrieval. Therefore, the effective and precise music …

Acoustic scene classification (ASC) using front-end timefrequency features and back-end
neural network classifiers has demonstrated good performance in recent years. However a …

The research problem addressed in this study is how to effectively combine multimodal data
from imperfect text transcripts and raw audio in a deep framework for automatic speech …

Audio signal processing is the most challenging field in the current era for an analysis of an
audio signal. Audio signal classification (ASC) comprises of generating appropriate features …

Audio classification is the task of identifying the sound categories that are associated with a
given audio signal. This paper presents an investigation on large-scale audio classification …