[HTML][HTML] 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 …
A survey on deep learning based forest environment sound classification at the edge
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 …
Unique natural and artificial phenomena pose severe threats to the perseverance of such …
New image dataset and new negative sample judgment method for crop pest recognition based on deep learning models
K Wang, K Chen, H Du, S Liu, J Xu, J Zhao, H Chen… - Ecological …, 2022 - Elsevier
Crop pests are responsible for serious economic loss around the worldwide. Accurate
recognition of pests is the key to pest control and is a considerable challenge in farming …
recognition of pests is the key to pest control and is a considerable challenge in farming …
Protomf: Prototype-based matrix factorization for effective and explainable recommendations
Recent studies show the benefits of reformulating common machine learning models
through the concept of prototypes–representatives of the underlying data, used to calculate …
through the concept of prototypes–representatives of the underlying data, used to calculate …
[HTML][HTML] Forest sound classification dataset: Fsc22
The study of environmental sound classification (ESC) has become popular over the years
due to the intricate nature of environmental sounds and the evolution of deep learning (DL) …
due to the intricate nature of environmental sounds and the evolution of deep learning (DL) …
[HTML][HTML] Sound classification and processing of urban environments: A systematic literature review
AFR Nogueira, HS Oliveira, JJM Machado… - Sensors, 2022 - mdpi.com
Audio recognition can be used in smart cities for security, surveillance, manufacturing,
autonomous vehicles, and noise mitigation, just to name a few. However, urban sounds are …
autonomous vehicles, and noise mitigation, just to name a few. However, urban sounds are …
A survey on artificial intelligence-based acoustic source identification
The concept of Acoustic Source Identification (ASI), which refers to the process of identifying
noise sources has attracted increasing attention in recent years. The ASI technology can be …
noise sources has attracted increasing attention in recent years. The ASI technology can be …
Prototype learning for interpretable respiratory sound analysis
Remote screening of respiratory diseases has been widely studied as a non-invasive and
early instrument for diagnosis purposes, especially in the pandemic. The respiratory sound …
early instrument for diagnosis purposes, especially in the pandemic. The respiratory sound …
Listen to interpret: Post-hoc interpretability for audio networks with nmf
This paper tackles post-hoc interpretability for audio processing networks. Our goal is to
interpret decisions of a trained network in terms of high-level audio objects that are also …
interpret decisions of a trained network in terms of high-level audio objects that are also …
Explaining speech classification models via word-level audio segments and paralinguistic features
Recent advances in eXplainable AI (XAI) have provided new insights into how models for
vision, language, and tabular data operate. However, few approaches exist for …
vision, language, and tabular data operate. However, few approaches exist for …