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A review of lightweight convolutional neural networks for ultrasound signal classification [PDF]
Frontiers in PhysiologyUltrasound signal processing plays an important role in medical image analysis. Embedded ultrasonography systems with low power consumption and high portability are suitable for disaster rescue, but due to the difficulty of ultrasonic signal recognition,
Bokun Zhang +5 more
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Optimizing Reservoir Computers for Signal Classification. [PDF]
Front Physiol, 2021 Reservoir computers are a type of recurrent neural network for which the network connections are not changed. To train the reservoir computer, a set of output signals from the network are fit to a training signal by a linear fit. As a result, training of a reservoir computer is fast, and reservoir computers may be built from analog hardware, resulting ...
Carroll TL.
europepmc +5 more sources
Intelligent and Converged Networks, 2021 Radio spectrum awareness, including understanding radio signal activities, is crucial for improving spectrum utilization, detecting security vulnerabilities, and supporting adaptive transmissions.
Yu Zhou +10 more
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Journal of Medical Signals and Sensors, 2022 Background: Drowsy driving is one of the leading causes of severe accidents worldwide. In this study, an analyzing method based on drowsiness level proposed to detect drowsiness through electroencephalography (EEG) measurements and vehicle dynamics data.
Sara Houshmand +2 more
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Real-Time Leak Detection for a Gas Pipeline Using a k-NN Classifier and Hybrid AE Features
Sensors, 2021 This paper introduces a technique using a k-nearest neighbor (k-NN) classifier and hybrid features extracted from acoustic emission (AE) signals for detecting leakages in a gas pipeline.
Thang Bui Quy, Jong-Myon Kim
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Adversarial Machine Learning for NextG Covert Communications Using Multiple Antennas
Entropy, 2022 This paper studies the privacy of wireless communications from an eavesdropper that employs a deep learning (DL) classifier to detect transmissions of interest.
Brian Kim +4 more
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An MDL-Based Wavelet Scattering Features Selection for Signal Classification
Axioms, 2022 Wavelet scattering is a redundant time-frequency transform that was shown to be a powerful tool in signal classification. It shares the convolutional architecture with convolutional neural networks, but it offers some advantages, including faster ...
Vittoria Bruni +2 more
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Distributed radar fusion and recurrent networks for classification of continuous human activities
IET Radar, Sonar & Navigation, 2022 Continuous Human Activity Recognition (HAR) in arbitrary directions is investigated in this paper using a network of five spatially distributed pulsed Ultra‐Wideband radars.
Ronny G. Guendel +2 more
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Two-Stage Ultrasound Signal Recognition Method Based on Envelope and Local Similarity Features
Machines, 2022 Accurate identification of ultrasonic signals can effectively improve the accuracy of a defect detection and inversion. Current methods, based on machine learning and deep learning have been able to classify signals with significant differences. However,
Liwei Wang +3 more
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STCDB: Signal Transduction Classification Database [PDF]
Nucleic Acids Research, 2004 The Signal Transduction Classification Database (STCDB) is a database of information relative to the classification of signal transduction. It is based primarily on a proposed classification of signal transduction and it describes each type of characterized signal transduction for which a unique ST number has been provided.
Chen, Ming +2 more
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