AIMC Topic: Sound

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Considerations and Challenges for Real-World Deployment of an Acoustic-Based COVID-19 Screening System.

Sensors (Basel, Switzerland)
Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. Acoustic-based artificial intelligence (AI) tools could provide a simple, scalable, and prompt method to screen for COVID-19 using easily acquirable ph...

Passive tracking of underwater acoustic targets based on multi-beam LOFAR and deep learning.

PloS one
Conventional passive tracking methods for underwater acoustic targets in sonar engineering generate time azimuth histogram and use it as a basis for target azimuth and tracking. Passive underwater acoustic targets only have azimuth information on the...

Non-intrusive deep learning-based computational speech metrics with high-accuracy across a wide range of acoustic scenes.

PloS one
Speech with high sound quality and little noise is central to many of our communication tools, including calls, video conferencing and hearing aids. While human ratings provide the best measure of sound quality, they are costly and time-intensive to ...

Measurements, Analysis, Classification, and Detection of Gunshot and Gunshot-like Sounds.

Sensors (Basel, Switzerland)
Gun violence has been on the rise in recent years. To help curb the downward spiral of this negative influence in communities, machine learning strategies on gunshot detection can be developed and deployed. After outlining the procedure by which a ty...

Feature Pyramid U-Net with Attention for Semantic Segmentation of Forward-Looking Sonar Images.

Sensors (Basel, Switzerland)
Forward-looking sonar is a technique widely used for underwater detection. However, most sonar images have underwater noise and low resolution due to their acoustic properties. In recent years, the semantic segmentation model U-Net has shown excellen...

Deblurring of Sound Source Orientation Recognition Based on Deep Neural Network.

Sensors (Basel, Switzerland)
Underwater target detection and identification technology are currently two of the most important research directions in the information disciplines. Traditionally, underwater target detection technology has struggled to meet the needs of current eng...

Empirical Mode Decomposition-Based Feature Extraction for Environmental Sound Classification.

Sensors (Basel, Switzerland)
In environment sound classification, log Mel band energies (MBEs) are considered as the most successful and commonly used features for classification. The underlying algorithm, fast Fourier transform (FFT), is valid under certain restrictions. In thi...

A Two-Mode Underwater Smart Sensor Object for Precision Aquaculture Based on AIoT Technology.

Sensors (Basel, Switzerland)
Monitoring the status of culture fish is an essential task for precision aquaculture using a smart underwater imaging device as a non-intrusive way of sensing to monitor freely swimming fish even in turbid or low-ambient-light waters. This paper deve...

A Parallel Classification Model for Marine Mammal Sounds Based on Multi-Dimensional Feature Extraction and Data Augmentation.

Sensors (Basel, Switzerland)
Due to the poor visibility of the deep-sea environment, acoustic signals are often collected and analyzed to explore the behavior of marine species. With the progress of underwater signal-acquisition technology, the amount of acoustic data obtained f...

A Prediction Model of Defecation Based on BP Neural Network and Bowel Sound Signal Features.

Sensors (Basel, Switzerland)
(1) Background: Incontinence and its complications pose great difficulties in the care of the disabled. Currently, invasive incontinence monitoring methods are too invasive, expensive, and bulky to be widely used. Compared with previous methods, bowe...