Results 1 to 10 of about 4,029,563 (257)

A review of lightweight convolutional neural networks for ultrasound signal classification [PDF]

Frontiers in Physiology
Ultrasound 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, Zhengping Li, Yuwen Hao, Lijun Wang, Xiaoxue Li, Yuan Yao   +5 more
doaj   +2 more sources

Radio spectrum awareness using deep learning: Identification of fading channels, signal distortions, medium access control protocols, and cellular systems

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, Hatim Alhazmi, Mohsen H. Alhazmi, Alhussain Almarhabi, Mofadal Alymani, Mingju He, Shengliang Peng, Abdullah Samarkandi, Zikang Sheng, Huaxia Wang, Yu-Dong Yao   +10 more
doaj   +1 more source

An Efficient Approach for Driver Drowsiness Detection at Moderate Drowsiness Level Based on Electroencephalography Signal and Vehicle Dynamics Data

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, Reza Kazemi, Hamed Salmanzadeh   +2 more
doaj   +1 more source

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
doaj   +1 more source

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, Yalin Sagduyu, Kemal Davaslioglu, Tugba Erpek, Sennur Ulukus   +4 more
doaj   +1 more source

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, Maria Lucia Cardinali, Domenico Vitulano   +2 more
doaj   +1 more source

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, Francesco Fioranelli, Alexander Yarovoy   +2 more
doaj   +1 more source

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, Senxiang Lu, Xiaoyuan Liu, Jinhai Liu   +3 more
doaj   +1 more source

Low-complexity DOA estimation method for a co-prime linear array

The Journal of Engineering, 2019
The problem of direction-of-arrival (DOA) estimation for a co-prime linear array is researched. A low-complexity DOA estimation method is proposed. The co-prime array is decomposed into two sparse uniform linear sub-arrays whose inter-element spacing ...
Xuchen Wu, Xiaopeng Yang, Bowen Han, Feng Xu   +3 more
doaj   +1 more source

Automated detection of myocardial infarction from ECG signal using variational mode decomposition based analysis

Healthcare Technology Letters, 2020
In this Letter, the authors propose a variational mode decomposition method for quantifying diagnostic information of myocardial infarction (MI) from the electrocardiogram (ECG) signal.
Ato Kapfo, Samarendra Dandapat, Prabin Kumar Bora   +2 more
doaj   +1 more source