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Cultivating Ensemble Diversity through Targeted Injection of Synthetic Data: Path Loss Prediction Examples

Electronics (Basel), 2024-02, Vol.13 (3), p.613

Sotiroudis, Sotirios P.

2024

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Fusing Diverse Input Modalities for Path Loss Prediction: A Deep Learning Approach

IEEE access, 2021, Vol.9, p.30441-30451

2021

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Music Deep Learning: Deep Learning Methods for Music Signal Processing-A Review of the State-of-the-Art

IEEE access, 2023, Vol.11, p.17031-17052

2023

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Low Complexity Deep Learning Framework for Greek Orthodox Church Hymns Classification

Applied sciences, 2023-08, Vol.13 (15), p.8638

2023

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From Spatial Urban Site Data to Path Loss Prediction: An Ensemble Learning Approach

IEEE transactions on antennas and propagation, 2022-07, Vol.70 (7), p.6101-6105

2022

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IEEE_Xplore

Evolutionary Ensemble Learning Pathloss Prediction for 4G and 5G Flying Base Stations with UAVs

IEEE transactions on antennas and propagation, 2023-07, Vol.71 (7), p.1-1

2023

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IEEE_Xplore

Deep learning for radio propagation: Using image-driven regression to estimate path loss in urban areas

ICT Express , 2020, 6(3), , pp.160-165

2020

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Patch Antenna Design using Artificial Intelligence Methods for 4G/5G Applications

2022 25th International Symposium on Wireless Personal Multimedia Communications (WPMC), 2022, p.497-500

2022

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IEEE_Xplore

Artificial Intelligence in Visible Light Positioning for Indoor IoT: A Methodological Review

IEEE open journal of the Communications Society, 2023, Vol.4, p.2838-2869

2023

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Enhancing Machine Learning Models for Path Loss Prediction Using Image Texture Techniques

IEEE antennas and wireless propagation letters, 2021-08, Vol.20 (8), p.1443-1447

2021

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IEEE_Xplore

Feature Importances: A Tool to Explain Radio Propagation and Reduce Model Complexity

Telecom (Basel), 2020-09, Vol.1 (2), p.114-125

2020

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Path Loss Prediction Modelling for Next-generation Internet-of-Things Applications Using Different Boosting Machine Learning Methods

2022 Panhellenic Conference on Electronics & Telecommunications (PACET), 2022, p.1-4

2022

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Music Deep Learning: A Survey on Deep Learning Methods for Music Processing

2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST), 2022, p.1-4

2022

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Application of a Composite Differential Evolution Algorithm in Optimal Neural Network Design for Propagation Path-Loss Prediction in Mobile Communication Systems

IEEE antennas and wireless propagation letters, 2013, Vol.12, p.364-367

2013

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IEEE_Xplore

Towards 6G: Deep Learning in Cell-Free Massive MIMO

2022 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), 2022, p.269-273

2022

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Neural Networks and Random Forests: A Comparison Regarding Prediction of Propagation Path Loss for NB-IoT Networks

2019 8th International Conference on Modern Circuits and Systems Technologies (MOCAST), 2019, p.1-4

2019

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Low Complexity Deep Learning Based Coordinated Beamforming for mmWave Massive MIMO Vehicular Networks

2024 Panhellenic Conference on Electronics & Telecommunications (PACET), 2024, p.1-4

2024

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A hybrid CNN-NGBoost model for probabilistic image-driven path loss prediction

2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI), 2022, p.898-899

2022

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IEEE_Xplore

Energy Consumption Assessment in Refrigeration Equipment: The SmartFridge Project

2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST), 2023, p.1-4

2023

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Path Loss Modeling for Flying Ad-Hoc Networks:An Ensemble Learning Approach

2023 17th European Conference on Antennas and Propagation (EuCAP), 2023, p.1-5

2023

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Modeling Received Power from 4G and 5G Networks in Greece U sing Machine Learning

2024 18th European Conference on Antennas and Propagation (EuCAP), 2024, p.1-5

2024

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Wideband Aperture-Coupled Array Design for Automotive Radar Applications

2024 18th European Conference on Antennas and Propagation (EuCAP), 2024, p.1-5

2024

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Ensemble Learning for 5G Flying Base Station Path Loss Modelling

2022 16th European Conference on Antennas and Propagation (EuCAP), 2022, p.1-4

2022

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Comparing Machine Learning Methods for Air-to-Ground Path Loss Prediction

2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST), 2021, p.1-4

2021

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The Challenges of Music Deep Learning for Traditional Music

2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST), 2023, p.1-5

2023

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Cultivating Ensemble Diversity through Targeted Injection of Synthetic Data: Path Loss Prediction Examples

Fusing Diverse Input Modalities for Path Loss Prediction: A Deep Learning Approach

Music Deep Learning: Deep Learning Methods for Music Signal Processing-A Review of the State-of-the-Art

Low Complexity Deep Learning Framework for Greek Orthodox Church Hymns Classification

From Spatial Urban Site Data to Path Loss Prediction: An Ensemble Learning Approach

Evolutionary Ensemble Learning Pathloss Prediction for 4G and 5G Flying Base Stations with UAVs

Deep learning for radio propagation: Using image-driven regression to estimate path loss in urban areas

Patch Antenna Design using Artificial Intelligence Methods for 4G/5G Applications

Artificial Intelligence in Visible Light Positioning for Indoor IoT: A Methodological Review

Enhancing Machine Learning Models for Path Loss Prediction Using Image Texture Techniques

Feature Importances: A Tool to Explain Radio Propagation and Reduce Model Complexity

Path Loss Prediction Modelling for Next-generation Internet-of-Things Applications Using Different Boosting Machine Learning Methods

Music Deep Learning: A Survey on Deep Learning Methods for Music Processing

Application of a Composite Differential Evolution Algorithm in Optimal Neural Network Design for Propagation Path-Loss Prediction in Mobile Communication Systems

Towards 6G: Deep Learning in Cell-Free Massive MIMO

Neural Networks and Random Forests: A Comparison Regarding Prediction of Propagation Path Loss for NB-IoT Networks

Low Complexity Deep Learning Based Coordinated Beamforming for mmWave Massive MIMO Vehicular Networks

A hybrid CNN-NGBoost model for probabilistic image-driven path loss prediction

Energy Consumption Assessment in Refrigeration Equipment: The SmartFridge Project

Path Loss Modeling for Flying Ad-Hoc Networks:An Ensemble Learning Approach

Modeling Received Power from 4G and 5G Networks in Greece U sing Machine Learning

Wideband Aperture-Coupled Array Design for Automotive Radar Applications

Ensemble Learning for 5G Flying Base Station Path Loss Modelling

Comparing Machine Learning Methods for Air-to-Ground Path Loss Prediction

The Challenges of Music Deep Learning for Traditional Music

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