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RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database
(
Elsevier B.V.
, 2019 , Article)
The omnipresence of unmanned aerial vehicles, or drones, among civilians can lead to technical, security, and public safety issues that need to be addressed, regulated and prevented. Security agencies are in continuous ...
Benchmark database for fine-grained image classification of benthic macroinvertebrates
(
Elsevier Ltd
, 2018 , Article)
Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and ...
NDDNet: a deep learning model for predicting neurodegenerative diseases from gait pattern
(
Springer Nature
, 2023 , Article)
Neurodegenerative diseases damage neuromuscular tissues and deteriorate motor neurons which affects the motor capacity of the patient. Particularly the walking gait is greatly influenced by the deterioration process. Early ...
Secrecy Outage Performance of Ground-to-Air Communications with Multiple Aerial Eavesdroppers and Its Deep Learning Evaluation
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
In this letter, we study the secure information transmission from a ground base station (GBS) to a legitimate unmanned aerial vehicle (UAV) user, in the presence of multiple UAV eavesdroppers. To enhance the secrecy ...
Convolutional Sparse Support Estimator-Based COVID-19 Recognition from X-Ray Images
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. ...
COVID-19 infection localization and severity grading from chest X-ray images
(
Elsevier Ltd
, 2021 , Article)
The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems incapable to diagnose and test patients at the required rate. Given the effects of COVID-19 on pulmonary tissues, chest radiographic ...
Real-Time Patient-Specific ECG Classification by 1D Self-Operational Neural Networks
(
IEEE Computer Society
, 2021 , Article)
Despite the proliferation of numerous deep learning methods proposed for generic ECG classification and arrhythmia detection, compact systems with the real-time ability and high accuracy for classifying patient-specific ...
A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications
(
Academic Press
, 2021 , Article Review)
Monitoring structural damage is extremely important for sustaining and preserving the service life of civil structures. While successful monitoring provides resolute and staunch information on the health, serviceability, ...
Robust biometric system using session invariant multimodal EEG and keystroke dynamics by the ensemble of self-ONNs
(
Elsevier Ltd
, 2022 , Article)
Harnessing the inherent anti-spoofing quality from electroencephalogram (EEG) signals has become a potential field of research in recent years. Although several studies have been conducted, still there are some vital ...
Early Bearing Fault Diagnosis of Rotating Machinery by 1D Self-Organized Operational Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Preventive maintenance of modern electric rotating machinery (RM) is critical for ensuring reliable operation, preventing unpredicted breakdowns and avoiding costly repairs. Recently many studies investigated machine ...