Data augmentation and deep learning methods in sound classification: A systematic review
OO Abayomi-Alli, R Damaševičius, A Qazi… - Electronics, 2022 - mdpi.com
The aim of this systematic literature review (SLR) is to identify and critically evaluate current
research advancements with respect to small data and the use of data augmentation …
research advancements with respect to small data and the use of data augmentation …
Acoustic scene classification: a comprehensive survey
Acoustic scene classification (ASC) has gained significant interest recently due to its diverse
applications. Various audio signal processing and machine learning methods have been …
applications. Various audio signal processing and machine learning methods have been …
Analyzing malaria disease using effective deep learning approach
K Sriporn, CF Tsai, CE Tsai, P Wang - Diagnostics, 2020 - mdpi.com
Medical tools used to bolster decision-making by medical specialists who offer malaria
treatment include image processing equipment and a computer-aided diagnostic system …
treatment include image processing equipment and a computer-aided diagnostic system …
A short-term load forecasting model based on mixup and transfer learning
Y Lu, G Wang, S Huang - Electric Power Systems Research, 2022 - Elsevier
When the amount of historical load data is insufficient, the use of deep learning for load
forecasting is prone to overfitting. This paper proposes a short-term electric load forecasting …
forecasting is prone to overfitting. This paper proposes a short-term electric load forecasting …
An investigation of fusion strategies for boosting pig cough sound recognition
Y Yin, N Ji, X Wang, W Shen, B Dai, S Kou… - … and Electronics in …, 2023 - Elsevier
The recognition of pig cough sounds is an effective way to monitor pig respiratory diseases
which seriously affect healthy pig breeding. Due to the complexity of the pig-housing …
which seriously affect healthy pig breeding. Due to the complexity of the pig-housing …
Acoustic scene classification based on Mel spectrogram decomposition and model merging
T Zhang, G Feng, J Liang, T An - Applied Acoustics, 2021 - Elsevier
Recently, excellent performance has been achieved in Acoustic Scene Classification (ASC)
by using Convolutional Neural Networks (CNNs) and Mel spectrogram feature …
by using Convolutional Neural Networks (CNNs) and Mel spectrogram feature …
Deep mutual attention network for acoustic scene classification
Fusion strategies that utilize time-frequency features have achieved superior performance in
acoustic scene classification tasks. However, the existing fusion schemes are mainly …
acoustic scene classification tasks. However, the existing fusion schemes are mainly …
Longitudinal tear detection method of conveyor belt based on audio-visual fusion
J Che, T Qiao, Y Yang, H Zhang, Y Pang - Measurement, 2021 - Elsevier
Conveyor belt tear detection is a very important part of coal mine safety production. In this
paper, a new method of detecting conveyor belt damage named audio-visual fusion (AVF) …
paper, a new method of detecting conveyor belt damage named audio-visual fusion (AVF) …
A novel acoustic scene classification model using the late fusion of convolutional neural networks and different ensemble classifiers
MA Alamir - Applied Acoustics, 2021 - Elsevier
Recent evidence suggests that convolutional neural networks (CNNs) can model acoustic
scene classification (ASC) with high accuracy. Ensemble classifiers have also shown high …
scene classification (ASC) with high accuracy. Ensemble classifiers have also shown high …
Binaural acoustic scene classification using wavelet scattering, parallel ensemble classifiers and nonlinear fusion
The analysis of ambient sounds can be very useful when developing sound base intelligent
systems. Acoustic scene classification (ASC) is defined as identifying the area of a recorded …
systems. Acoustic scene classification (ASC) is defined as identifying the area of a recorded …