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Retraction Notice: Sound Classification Using Python [PDF]

open access: yesITM Web of Conferences, 2021
We take a zero tolerance to any situation where fraudulent research is published in our journals. As a result, this article has been retracted by the Publisher because it is suspected to be a nonsensical computer-generated publication with a number of ...
Jadhav Swapnil, Karpe Sarvesh, Das Siuli
doaj   +1 more source

Practical Inter-Floor Noise Sensing System with Localization and Classification

open access: yesSensors, 2019
Inter-floor noise is a severe social problem which causes illegal arson, violence, and even murder. In this paper, an inter-floor noise sensing system is proposed to detect and record information related to inter-floor noise in an apartment building. The
Junho Son, Chong-Min Kyung, Hyuntae Cho
doaj   +1 more source

Deep Learning-Based Cattle Vocal Classification Model and Real-Time Livestock Monitoring System with Noise Filtering

open access: yesAnimals, 2021
The priority placed on animal welfare in the meat industry is increasing the importance of understanding livestock behavior. In this study, we developed a web-based monitoring and recording system based on artificial intelligence analysis for the ...
Dae-Hyun Jung   +9 more
doaj   +1 more source

A System for Heart Sounds Classification

open access: yesPLoS ONE, 2014
The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases - one of the major causes of death around the globe - a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution.
Gradolewski, Dawid   +2 more
openaire   +4 more sources

Automatic Environmental Sound Recognition: Performance versus Computational Cost [PDF]

open access: yes, 2016
In the context of the Internet of Things (IoT), sound sensing applications are required to run on embedded platforms where notions of product pricing and form factor impose hard constraints on the available computing power.
Krstulovic, Sacha   +3 more
core   +2 more sources

Evaluation of classical machine learning techniques towards urban sound recognition embedded systems [PDF]

open access: yes, 2019
Automatic urban sound classification is a desirable capability for urban monitoring systems, allowing real-time monitoring of urban environments and recognition of events.
Braeken, An   +3 more
core   +1 more source

Environmental Sound Classification with Parallel Temporal-spectral Attention

open access: yes, 2020
Convolutional neural networks (CNN) are one of the best-performing neural network architectures for environmental sound classification (ESC). Recently, temporal attention mechanisms have been used in CNN to capture the useful information from the ...
Chong, Dading   +3 more
core   +1 more source

Classification of Similar Impact Sounds [PDF]

open access: yes, 2010
Several sound classifiers have been developed throughout the years. The accuracy provided by these classifiers is influenced by the features they use and the classification method implemented. While there are many approaches in sound feature extraction and in sound classification, most have been used to classify sounds with very different ...
Sofia Cavaco, José Rodeia
openaire   +1 more source

Sound Event Detection in Underground Parking Garage Using Convolutional Neural Network

open access: yesBig Data and Cognitive Computing, 2020
Parking is a crucial element in urban mobility management. The availability of parking areas makes it easier to use a service, determining its success. Proper parking management allows economic operators located nearby to increase their business revenue.
Giuseppe Ciaburro
doaj   +1 more source

A Robust Interpretable Deep Learning Classifier for Heart Anomaly Detection Without Segmentation

open access: yes, 2020
Traditionally, abnormal heart sound classification is framed as a three-stage process. The first stage involves segmenting the phonocardiogram to detect fundamental heart sounds; after which features are extracted and classification is performed.
Denman, Simon   +5 more
core   +1 more source

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