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ORCIDVassilis Alimisis
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2020 – today
- 2024
[j6]Christos Dimas
, Vassilis Alimisis, Nikolaos K. Uzunoglu, Paul P. Sotiriadis:
Advances in Electrical Impedance Tomography Inverse Problem Solution Methods: From Traditional Regularization to Deep Learning. IEEE Access 12: 47797-47829 (2024)- [j5]Vassilis Alimisis, Dimitrios G. Arnaoutoglou, Emmanouil Anastasios Serlis, Argyro Kamperi, Konstantinos Metaxas, George A. Kyriacou, Paul P. Sotiriadis:
A Radar-Based System for Detection of Human Fall Utilizing Analog Hardware Architectures of Decision Tree Model. IEEE Open J. Circuits Syst. 5: 224-242 (2024) - [j4]Vassilis Alimisis, Emmanouil Anastasios Serlis, Andreas Papathanasiou, Nikolaos P. Eleftheriou, Paul P. Sotiriadis:
Power-Efficient Analog Hardware Architecture of the Learning Vector Quantization Algorithm for Brain Tumor Classification. IEEE Trans. Very Large Scale Integr. Syst. 32(11): 1969-1982 (2024) - [c22]Vassilis Alimisis, Andreas Papathanasiou, Georgios Georgousis, Paul P. Sotiriadis:
An Analog Neural Network for Estimating Sea State or Wave Height from Inertial Sensor Data. AICAS 2024: 238-242 - [c21]Vassilis Alimisis, Argyro Kamperi, Georgios Gennis, Paul P. Sotiriadis:
A Precise, Power-Efficient, Analog-Hardware Edge Detector for Biomedical Imaging. ISBI 2024: 1-5 - [c20]Christos Dimas, Vassilis Alimisis, Nikolaos K. Uzunoglu, Paul P. Sotiriadis:
A Moment-Based Weighted Block Sparse Bayesian Learning Approach for Simultaneous Dual-Layer Lung Electrical Impedance Tomography. ISBI 2024: 1-5 - [c19]Vassilis Alimisis, Andreas Papathanasiou, Konstantinos Cheliotis, Nikolaos P. Eleftheriou, Paul P. Sotiriadis:
An Analog Classifier for Liver Disorders based on Centroid Machine Learning Model. MOCAST 2024: 1-4 - [c18]Vassilis Alimisis, Andreas Papathanasiou, Konstantinos Cheliotis, Nikolaos P. Eleftheriou, Paul P. Sotiriadis:
A Memristor-Equivalent Analog Integrated Neural Network for Air Quality Classification. MOCAST 2024: 1-4 - [c17]Nikolaos P. Eleftheriou, Vassilis Alimisis, Paul P. Sotiriadis:
Low-Power Single-Stage Programmable CMOS LNA for Ku-Band Applications. MOCAST 2024: 1-4 - [c16]Vassilis Alimisis, Charis Aletraris, Andreas Papathanasiou, Paul P. Sotiriadis:
A Robot Execution Failures Classification System Based on Analog IC Neural Networks. PRIME 2024: 1-4 - 2023
- [j3]Vassilis Alimisis, Georgios Gennis, Marios Gourdouparis, Christos Dimas, Paul P. Sotiriadis:
A Low-Power Analog Integrated Implementation of the Support Vector Machine Algorithm with On-Chip Learning Tested on a Bearing Fault Application. Sensors 23(8): 3978 (2023) - [c15]Vassilis Alimisis, Nikolaos P. Eleftheriou, Paul P. Sotiriadis:
A Low-Power Analog Integrated Gaussian-based Neural Network Classifier with Application to Hepatitis Disease Recognition. ICM 2023: 172-177 - [c14]Vassilis Alimisis, Nikolaos P. Eleftheriou, Paul P. Sotiriadis:
A Low-Power Analog Integrated Deep Spatio-Temporal Inference Network with Application to Digit Classification. ICM 2023: 280-283 - [c13]Vassilis Alimisis, Nikolaos P. Eleftheriou, Savvas Leventikidis, Paul P. Sotiriadis:
An Analog Integrated, Low-Power, Area-Efficient, Gilbert, Modulo-based Classifier with Application to Lung-Cancer Classification. ICM 2023: 317-320 - [c12]Georgios Gennis, Argyro Kamperi, Vassilis Alimisis, Christos Dimas, Paul P. Sotiriadis:
An Area-Efficient, Analog Integrated Image Edge Detector based on the Robert's Cross Operator. MOCAST 2023: 1-4 - 2022
- [j2]Vassilis Alimisis, Georgios Gennis, Konstantinos Touloupas, Christos Dimas, Marios Gourdouparis, Paul P. Sotiriadis:
Gaussian Mixture Model classifier analog integrated low-power implementation with applications in fault management detection. Microelectron. J. 126: 105510 (2022) - [c11]Christos Dimas, Vassilis Alimisis, Paul P. Sotiriadis:
Electrical Impedance Tomography using a Weighted Bound-Optimization Block Sparse Bayesian Learning Approach. BIBE 2022: 243-248 - [c10]Vassilis Alimisis, Georgios Gennis, Errikos Tsouvalas, Christos Dimas, Paul P. Sotiriadis:
An Analog, Low-Power Threshold Classifier tested on a Bank Note Authentication Dataset. ICM 2022: 66-69 - 2021
- [j1]Dimitrios Baxevanakis, Vassilis Alimisis, Paul P. Sotiriadis:
An intermodulation distortion estimation method for linear CMOS circuits. Int. J. Circuit Theory Appl. 49(5): 1244-1260 (2021) - [c9]Vassilis Alimisis, Georgios Gennis, Christos Dimas, Paul P. Sotiriadis:
An Analog Bayesian Classifier Implementation, for Thyroid Disease Detection, based on a Low-Power, Current-Mode Gaussian Function Circuit. ICM 2021: 153-156 - [c8]Vassilis Alimisis, Marios Gourdouparis, Christos Dimas, Paul P. Sotiriadis:
Ultra-Low Power, Low-Voltage, Fully-Tunable, Bulk-Controlled Bump Circuit. MOCAST 2021: 1-4 - 2020
- [c7]Vassilis Alimisis, Marios Gourdouparis, Christos Dimas, Paul P. Sotiriadis:
Implementation of Fractional-order Model of Nickel-Cadmium Cell using Current Feedback Operational Amplifiers. ECCTD 2020: 1-4 - [c6]Christos Dimas, Vassilis Alimisis, Paul P. Sotiriadis:
SPICE and MATLAB simulation and evaluation of Electrical Impedance Tomography readout chain using phantom equivalents. ECCTD 2020: 1-4 - [c5]Vassilis Alimisis, Christos Dimas, Paul P. Sotiriadis:
Analogue Realization of Fractional-Order Healthy and Cancerous Lung Cell Models for Electrical Impedance Spectroscopy. ICM 2020: 1-4 - [c4]Georgios Pappas, Vassilis Alimisis, Christos Dimas, Paul P. Sotiriadis:
Analogue Realization of a Fully Tunable Fractional-Order PID Controller for a DC Motor. ICM 2020: 1-4 - [c3]Vassilis Alimisis, Georgios Pappas, Paul P. Sotiriadis:
Fractional-Order Instrumentation Amplifier Transfer Function for Control Applications. SBCCI 2020: 1-6
2010 – 2019
- 2019
- [c2]Vassilis Alimisis, Panagiotis Bertsias, Costas Psychalinos, Ahmed S. Elwakil:
Electronically Tunable Implementation of the Arterial Viscoelasticity Model. TSP 2019: 145-148 - 2018
- [c1]Emmanuel A. Gonzalez, Vassilis Alimisis, Costas Psychalinos, Aleksei Tepljakov:
Design of a Generalized Fractional-Order PID Controller Using Operational Amplifiers. ICECS 2018: 253-256
Coauthor Index
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last updated on 2024-12-02 22:30 CET by the dblp team
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