S. Georgakopoulos

发表

Enhancing the Human Health Status Prediction: The ATHLOS Project

Aristidis G. Vrahatis, F. F. Caballero, J. Ayuso-Mateos, 2021, medRxiv.

Supervised Dimensionality Reduction and Classification with Convolutional Autoencoders

V. Plagianakos, Ioannis Nellas, S. Tasoulis, 2022, ArXiv.

Supervised Dimensionality Reduction and Classification with Convolutional Autoencoders

V. Plagianakos, Ioannis Nellas, S. Tasoulis, 2022, ArXiv.

Deep Hybrid Learning for Anomaly Detection in Behavioral Monitoring

Aristidis G. Vrahatis, Sotiris K. Tasoulis, V. Plagianakos, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

Supervised Dimensionality Reduction and Image Classification Utilizing Convolutional Autoencoders

V. Plagianakos, S. Tasoulis, S. Georgakopoulos, 2022, 2208.12152.

Convolutional Neural Networks for Pose Recognition in Binary Omni-directional Images

Vassilis P. Plagianakos, Kostas Delibasis, Spiros V. Georgakopoulos, 2016, AIAI.

A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project

F. F. Caballero, J. Ayuso-Mateos, V. Plagianakos, 2022, Health Information Science and Systems.

A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project

Aristidis G. Vrahatis, F. F. Caballero, J. Ayuso-Mateos, 2022, Health Information Science and Systems.

Visualizing High-dimensional single-cell RNA-sequencing data through multiple Random Projections

Vassilis P. Plagianakos, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Biomedical Data Ensemble Classification using Random Projections

Vassilis P. Plagianakos, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Efficient Learning Rate Adaptation for Convolutional Neural Network Training

Vassilis P. Plagianakos, Spiros V. Georgakopoulos, V. Plagianakos, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Convolutional Neural Networks for Twitter Text Toxicity Analysis

Vassilis P. Plagianakos, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, 2019, INNSBDDL.

A software tool for the automatic detection and quantification of fibrotic tissues in microscopy images

S.V. Georgakopoulos, I. Maglogiannis, S.K. Tasoulis, 2015, Inf. Sci..

Pose recognition using convolutional neural networks on omni-directional images

Vassilis P. Plagianakos, Kostas Delibasis, Spiros V. Georgakopoulos, 2017, Neurocomputing.

Geodesically-corrected Zernike descriptors for pose recognition in omni-directional images

Vassilis P. Plagianakos, Kostas Delibasis, Spiros V. Georgakopoulos, 2016, Integr. Comput. Aided Eng..

Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification

Dimitris K. Iakovidis, Vassilis P. Plagianakos, Spiros V. Georgakopoulos, 2018, IEEE Transactions on Medical Imaging.

Detection of Fake Generated Scientific Abstracts

V. Plagianakos, S. Tasoulis, S. Georgakopoulos, 2023, 2023 IEEE Ninth International Conference on Big Data Computing Service and Applications (BigDataService).

Text Analysis of COVID-19 Tweets

V. Plagianakos, S. Tasoulis, S. Georgakopoulos, 2022, International Conference on Engineering Applications of Neural Networks.

Convolutional Neural Networks for Toxic Comment Classification

Vassilis P. Plagianakos, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, 2018, SETN.

Change detection and convolution neural networks for fall recognition

Vassilis P. Plagianakos, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, 2020, Neural Computing and Applications.

Deep Learning and Change Detection for Fall Recognition

Vassilis P. Plagianakos, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, 2019, EANN.

Analysing sentiment change detection of Covid-19 tweets

Sotiris K. Tasoulis, V. Plagianakos, S. Georgakopoulos, 2023, Neural Computing and Applications.

Artificial Neural Networks and Principal Components Analysis for Detection of Idiopathic Pulmonary Fibrosis in Microscopy Images

Vassilis P. Plagianakos, Spiros V. Georgakopoulos, Ilias Maglogiannis, 2013, EANN.

Real Time Sentiment Change Detection of Twitter Data Streams

Vassilis P. Plagianakos, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, 2018, 2018 Innovations in Intelligent Systems and Applications (INISTA).

Single-cell regulatory network inference and clustering from high-dimensional sequencing data

Vassilis P. Plagianakos, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Unsupervised Learning for Large Scale Data: The ATHLOS Project

F. F. Caballero, J. Ayuso-Mateos, D. Panagiotakos, 2021, medRxiv.

Health in All Policy Making Utilizing Big Data

V. Plagianakos, D. Kyriazis, S. Georgakopoulos, 2020, Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH.

Ensemble Classification through Random Projections for single-cell RNA-seq data

Aristidis G. Vrahatis, Vassilis Plagianakos, Sotiris Tasoulis, 2020, bioRxiv.

Assessing Image Analysis Filters as Augmented Input to Convolutional Neural Networks for Image Classification

Vassilis P. Plagianakos, Kostas Delibasis, Spiros V. Georgakopoulos, 2018, ICANN.

Improving the performance of convolutional neural network for skin image classification using the response of image analysis filters

V. Plagianakos, K. Delibasis, Ilias Maglogiannis, 2018, Neural Computing and Applications.

Unsupervised Learning for Large Scale Data: The ATHLOS Project

Aristidis G. Vrahatis, J. Ayuso-Mateos, V. Plagianakos, 2021, medRxiv.

Two phase cooperative learning for supervised dimensionality reduction

V. Plagianakos, S. Tasoulis, S. Georgakopoulos, 2023, Pattern Recognit..

Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification

Michael D. Vasilakakis, V. Plagianakos, D. Iakovidis, 2018, IEEE Transactions on Medical Imaging.

Neural Networks Voting for Projection Based Ensemble Classifiers

V. Plagianakos, S. Tasoulis, S. Georgakopoulos, 2023, 2023 IEEE International Conference on Big Data (BigData).

Investigating the overlap of machine learning algorithms in the final results of RNA-seq analysis on gene expression estimation

V. Plagianakos, S. Tasoulis, S. Georgakopoulos, 2024, Health Inf. Sci. Syst..