A review of deep learning based methods for acoustic scene classification

J Abeßer - Applied Sciences, 2020 - mdpi.com
The number of publications on acoustic scene classification (ASC) in environmental audio
recordings has constantly increased over the last few years. This was mainly stimulated by …

A survey on preprocessing and classification techniques for acoustic scene

VK Singh, K Sharma, SN Sur - Expert Systems with Applications, 2023 - Elsevier
There are lots of research papers for ASC, and in recent years it is rapidly increasing.
DCASE also provides different types of competition for the submission of several papers to …

Integrating the data augmentation scheme with various classifiers for acoustic scene modeling

H Chen, Z Liu, Z Liu, P Zhang, Y Yan - arXiv preprint arXiv:1907.06639, 2019 - arxiv.org
This technical report describes the IOA team's submission for TASK1A of DCASE2019
challenge. Our acoustic scene classification (ASC) system adopts a data augmentation …

Late fusion framework for Acoustic Scene Classification using LPCC, SCMC, and log-Mel band energies with Deep Neural Networks

C Paseddula, SV Gangashetty - Applied Acoustics, 2021 - Elsevier
A major problem in Acoustic Scene Classification (ASC) is a representation of an acoustic
scene, which serves to be an important task for ASC. This study used Linear Prediction …

Classification of hand gestures based on multi-channel EMG by scale Average wavelet transform and convolutional neural network

DC Oh, YU Jo - International Journal of Control, Automation and …, 2021 - Springer
Predicting and accurately classifying intentions for human hand gestures can be used not
only for active prosthetic hands, rehabilitation robots and entertainment robots but also for …

Deep mutual attention network for acoustic scene classification

W Xie, Q He, Z Yu, Y Li - Digital Signal Processing, 2022 - Elsevier
Fusion strategies that utilize time-frequency features have achieved superior performance in
acoustic scene classification tasks. However, the existing fusion schemes are mainly …

Classification of motor functions from electroencephalogram (EEG) signals based on an integrated method comprised of common spatial pattern and wavelet …

N Yahya, H Musa, ZY Ong, I Elamvazuthi - Sensors, 2019 - mdpi.com
In this work, an algorithm for the classification of six motor functions from an
electroencephalogram (EEG) signal that combines a common spatial pattern (CSP) filter and …

Epileptic seizure detection using spectral transformation and convolutional neural networks

TS Cleatus, M Thungamani - Journal of The Institution of Engineers (India) …, 2022 - Springer
Automatic seizure detection and classification of seizures, as well as identification of pre-
ictal activity in the electroencephalogram (EEG), are extremely important in clinical research …

A study of features and deep neural network architectures and hyper-parameters for domestic audio classification

A Copiaco, C Ritz, N Abdulaziz, S Fasciani - Applied Sciences, 2021 - mdpi.com
Featured Application The algorithms explored in this research can be used for any multi-
level classification applications. Abstract Recent methodologies for audio classification …

Multi-level attention model with deep scattering spectrum for acoustic scene classification

Z Li, Y Hou, X Xie, S Li, L Zhang… - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Acoustic scene classification (ASC) refers to the classification of audio into one of predefined
classes that characterize the environment. People are used to combine log-mel filterbank …