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Sajjad Afrakhteh
Sajjad Afrakhteh
Other namesS. Afrakhteh
Senior Postdoctoral Researcher at University of Trento, Italy
Verified email at unitn.it - Homepage
Title
Cited by
Cited by
Year
Accurate classification of EEG signals using neural networks trained by hybrid population-physic-based algorithm
S Afrakhteh, MR Mosavi, M Khishe, A Ayatollahi
Machine Intelligence Research 17, 108-122, 2020
472020
An efficient method for classifying motor imagery using CPSO-trained ANFIS prediction
MR Mosavi, A Ayatollahi, S Afrakhteh
Evolving systems 12 (2), 319-336, 2021
242021
Applying an efficient evolutionary algorithm for EEG signal feature selection and classification in decision-based systems
S Afrakhteh, MR Mosavi
Energy Efficiency of Medical Devices and Healthcare Applications, 25-52, 2020
232020
Coherent Plane Wave Compounding Combined with Tensor Completion Applied for Ultrafast Imaging
S Afrakhteh, H Behnam
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 68 …, 2021
172021
High-resolution and high-contrast ultrafast ultrasound imaging using coherent plane wave adaptive compounding
M Hashemseresht, S Afrakhteh, H Behnam
Biomedical Signal Processing and Control 73, 103446, 2022
162022
Benchmark methodological approach for the application of artificial intelligence to lung ultrasound data from COVID-19 patients: From frame to prognostic-level
U Khan, S Afrakhteh, F Mento, N Fatima, L De Rosa, LL Custode, Z Azam, ...
Ultrasonics 132, 106994, 2023
142023
Low-complexity adaptive minimum variance ultrasound beam-former based on diagonalization
S Afrakhteh, H Behnam
Biomedical Signal Processing and Control 62, 102110, 2020
122020
Efficient Synthetic Transmit Aperture Ultrasound based on Tensor Completion
S Afrakhteh, H Behnam
Ultrasonics 117, 106553, 2021
112021
A fast and high frame rate adaptive beamforming using DCT‐based RF‐line recovery in line‐by‐line ultrasound imaging
S Afrakhteh, H Behnam
International Journal of Imaging Systems and Technology 30 (4), 1080-1094, 2020
112020
An efficient method for selecting the optimal features using evolutionary algorithms for epilepsy diagnosis
S Afrakhteh, MR Mosavi
Journal of Circuits, Systems and Computers 29 (12), 2050195, 2020
112020
Increasing frame rate of echocardiography based on a novel 2D spatio-temporal meshless interpolation
H Jalilian, S Afrakhteh, G Iacca, L Demi
Ultrasonics 131, 106953, 2023
102023
Temporal super-resolution of echocardiography using a novel high-precision non-polynomial interpolation
S Afrakhteh, H Jalilian, G Iacca, L Demi
Biomedical Signal Processing and Control 78, 104003, 2022
92022
Sleep apnea detection from ECG signal using deep CNN-based structures
A Ayatollahi, S Afrakhteh, F Soltani, E Saleh
Evolving Systems, 1-16, 2022
72022
Increasing the Frame Rate of Echocardiography Images Based on a Novel Interpolation Technique
S Afrakhteh, H Jalilian, G Iacca, L Demi
2022 IEEE International Ultrasonics Symposium (IUS), 1-4, 2022
62022
Classification of sleep apnea using EMD-based features and PSO-trained neural networks
S Afrakhteh, A Ayatollahi, F Soltani
Biomedical Engineering/Biomedizinische Technik 66 (5), 459-472, 2021
62021
Multi-task EEG Signal Classification using Correlation-based IMF Selection and Multi-class CSP
N Alizadeh, S Afrakhteh, MR Mosavi
IEEE Access, 2023
42023
High Frame Rate Ultrasound Imaging by Means of Tensor Completion: Application to Echocardiography
S Afrakhteh, G Iacca, L Demi
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 70 …, 2022
42022
Classification of two motor imagery based on EEG signals in brain computer interface systems using LDA, SVM and GMM methods
S Afrakhteh, A Amirkhani, MR Mosavi, A Ayatollahi
Proceedings of the 1st International Conference on Application of Research …, 2016
42016
Increasing Frame Rate of Focused Ultrasound Imaging Based on Tensor Completion
S Afrakhteh, G Iacca, L Demi
2022 IEEE International Ultrasonics Symposium (IUS), 1-4, 2022
32022
Automatic Scoring of COVID-19 LUS Videos Using Cross-correlation-Based Features Aggregated from Frame-Level Confidence Levels Obtained by a Pre-trained Deep Neural Network
S Afrakhteh, F Mento, U Khan, L De Rosa, N Fatima, Z Azam, F Tursi, ...
2022 IEEE International Ultrasonics Symposium (IUS), 1-3, 2022
22022
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