AIMC Topic: Acoustics

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Machine Learning Estimation of the Phase at the Fading Points of an OFDR-Based Distributed Sensor.

Sensors (Basel, Switzerland)
The paper reports a machine learning approach for estimating the phase in a distributed acoustic sensor implemented using optical frequency domain reflectometry, with enhanced robustness at the fading points. A neural network configuration was traine...

ANIMAL-SPOT enables animal-independent signal detection and classification using deep learning.

Scientific reports
Bioacoustic research spans a wide range of biological questions and applications, relying on identification of target species or smaller acoustic units, such as distinct call types. However, manually identifying the signal of interest is time-intensi...

Optimal Underwater Acoustic Warfare Strategy Based on a Three-Layer GA-BP Neural Network.

Sensors (Basel, Switzerland)
A defense platform is usually based on two methods to make underwater acoustic warfare strategy decisions. One is through Monte-Carlo method online simulation, which is slow. The other is by typical empirical (database) and typical back-propagation (...

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...

LPAI-A Complete AIoT Framework Based on LPWAN Applicable to Acoustic Scene Classification Scenarios.

Sensors (Basel, Switzerland)
Deploying artificial intelligence on edge nodes of Low-Power Wide Area Networks can significantly reduce network transmission volumes, event response latency, and overall network power consumption. However, the edge nodes in LPWAN bear limited comput...

Non-Contact Vibro-Acoustic Object Recognition Using Laser Doppler Vibrometry and Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Laser Doppler vibrometers (LDVs) have been widely adopted due to their large number of benefits in comparison to traditional contacting vibration transducers. Their high sensitivity, among other unique characteristics, has also led to their use as op...

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 ...

Deep Learning-Based Framework for Fast and Accurate Acoustic Hologram Generation.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Acoustic holography has been gaining attention for various applications, such as noncontact particle manipulation, noninvasive neuromodulation, and medical imaging. However, only a few studies on how to generate acoustic holograms have been conducted...

Deep Scattering Spectrum Germaneness for Fault Detection and Diagnosis for Component-Level Prognostics and Health Management (PHM).

Sensors (Basel, Switzerland)
Most methodologies for fault detection and diagnosis in prognostics and health management (PHM) systems use machine learning (ML) or deep learning (DL), in which either some features are extracted beforehand (in the case of typical ML approaches) or ...