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Vassilis P. Plagianakos

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

47

Venues

12

Active years

1999–2025

Best venue rank

A*

Where they publish

Papers

47 indexed papers, newest first.

YearVenueTitleAuthors
2025CIBCBEnhancing Machine Learning Models for Medical Coding: Diagnostic Codes Mapping and Synthetic Clinical Notes.Aikaterini Bilioni, Panagiotis Anagnostou, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos
2025CIBCBShort-term impacts of weather conditions on biomarkers among urban adults in Greece.Katerina Tsiaktani, Panagiotis Anagnostou, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, John A. Gittings, Dionysios E. Raitsos, Athanasia Sergounioti, Vassilis P. Plagianakos
2025EMNLPKrikri: Advancing Open Large Language Models for Greek.Dimitris Roussis, Leon Voukoutis, Georgios Paraskevopoulos, Sokratis Sofianopoulos, Prokopis Prokopidis, Vassilis P. Plagianakos, Athanasios Katsamanis, Stelios Piperidis, Vassilis Katsouros
2024CECHyperdimensional Computing Approaches in Single Cell RNA Sequencing Classification.Petros Barmpas, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos
2024CECHarnessing LSTMs for Enhanced Prediction of Psychotic Episodes in Schizophrenia Spectrum.Paraskevi V. Tsakmaki, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos
2024CIBCBLeveraging Large Language Models for Information Extraction: Identifying microRNA - Gene Interactions in Biomedical Literature.Steve Stavropoulos, Elissavet Zacharopoulou, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Vassilis P. Plagianakos, Artemis G. Hatzigeorgiou
2024EANNHCER: Hierarchical Clustering-Ensemble Regressor.Petros Barmpas, Panagiotis Anagnostou, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos
2024EANNMachine Learning-Driven Improvements in HRV Artifact Correction for Psychosis Prediction in the Schizophrenia Spectrum.Paraskevi V. Tsakmaki, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos
2023DCOSSAn Efficient and Lightweight Commitment Scheme for IoT Data Streams.Angeliki Katsika, Konstantinos Papageorgiou, Alexandros Fakis, Vassilis P. Plagianakos, Georgios P. Spathoulas
2023GLOBECOMInvestigating Feasibility of Stress Detection from Social Media Content Through Wearables.Kalliopi Tsiampa, Lili Zhu, Petros Spachos, Vassilis P. Plagianakos
2022EANNText Analysis of COVID-19 Tweets.Panagiotis C. Theocharopoulos, Anastasia Tsoukala, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Vassilis P. Plagianakos
2022IJCNNDeep Hybrid Learning for Anomaly Detection in Behavioral Monitoring.Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Aristidis G. Vrahatis, Serafeim P. Moustakidis, Dimitrios Tsaopoulos, Vassilis P. Plagianakos
2020EANNOn Image Prefiltering for Skin Lesion Characterization Utilizing Deep Transfer Learning.Kostas Delibasis, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Ilias Maglogiannis, Vassilis P. Plagianakos
2019BIBEEnhancing Clustering of Single-Cell RNA-Seq Data by Proximity Learning on Random Projected Spaces.Aristidis G. Vrahatis, Georgios N. Dimitrakopoulos, Sotiris K. Tasoulis, Vassilis P. Plagianakos
2019CIBCBA single-cell Systems Biology approach for disease-specific subpathway extraction.Aristidis G. Vrahatis, Georgios N. Dimitrakopoulos, Sotiris K. Tasoulis, Vassilis P. Plagianakos
2019CIBCBVisualizing High-Dimensional Single-Cell RNA-seq Data via Random Projections and Geodesic Distances.Aristidis G. Vrahatis, Sotiris K. Tasoulis, Georgios N. Dimitrakopoulos, Vassilis P. Plagianakos
2019EANNDeep Learning and Change Detection for Fall Recognition.Sotiris K. Tasoulis, Georgios I. Mallis, Spiros V. Georgakopoulos, Aristidis G. Vrahatis, Vassilis P. Plagianakos, Ilias G. Maglogiannis
2019IJCNNEfficient Learning Rate Adaptation for Convolutional Neural Network Training.Spiros V. Georgakopoulos, Vassilis P. Plagianakos
2018ICANNAssessing Image Analysis Filters as Augmented Input to Convolutional Neural Networks for Image Classification.Kostas Delibasis, Ilias Maglogiannis, Spiros V. Georgakopoulos, Konstantina Kottari, Vassilis P. Plagianakos
2018INISTAReal Time Sentiment Change Detection of Twitter Data Streams.Sotiris K. Tasoulis, Aristidis G. Vrahatis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos
2017EANNDetection of Malignant Melanomas in Dermoscopic Images Using Convolutional Neural Network with Transfer Learning.Spiros V. Georgakopoulos, Konstantina Kottari, Kostas Delibasis, Vassilis P. Plagianakos, Ilias Maglogiannis
2017EANNA Novel Adaptive Learning Rate Algorithm for Convolutional Neural Network Training.Spiros V. Georgakopoulos, Vassilis P. Plagianakos
2014CECUnsupervised clustering and multi-optima evolutionary search.Vassilis P. Plagianakos
2013BIBEHuman segmentation and pose recognition in fish-eye video for assistive environments.Konstantinos K. Delibasis, Vassilis P. Plagianakos, Theodosios Goudas, Ilias Maglogiannis
2013CECMulti-optima search using Differential Evolution and unsupervised clustering.Vassilis P. Plagianakos
2013EANNArtificial Neural Networks and Principal Components Analysis for Detection of Idiopathic Pulmonary Fibrosis in Microscopy Images.Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Vassilis P. Plagianakos, Ilias Maglogiannis
2012CECMultimodal optimization using niching differential evolution with index-based neighborhoods.Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis
2012CECTracking Particle Swarm Optimizers: An adaptive approach through multinomial distribution tracking with exponential forgetting.Michael G. Epitropakis, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis
2012CECDensity based Projection Pursuit Clustering.Sotiris K. Tasoulis, Michael G. Epitropakis, Vassilis P. Plagianakos, Dimitris K. Tasoulis
2010CECEvolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution.Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis
2010CECEvolutionary Principal Direction Divisive Partitioning.Sotiris K. Tasoulis, Dimitris K. Tasoulis, Vassilis P. Plagianakos
2009CECEvolutionary adaptation of the differential evolution control parameters.Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis
2008CECBalancing the exploration and exploitation capabilities of the Differential Evolution Algorithm.Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis
2008GECCONon-monotone differential evolution.Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis
2007CECComputational intelligence algorithms for risk-adjusted trading strategies.Nicos G. Pavlidis, E. G. Pavlidis, Michael G. Epitropakis, Vassilis P. Plagianakos, Michael N. Vrahatis
2006CECHuman Designed Vs. Genetically Programmed Differential Evolution Operators.Nicos G. Pavlidis, Vassilis P. Plagianakos, Dimitris K. Tasoulis, Michael N. Vrahatis
2005CECClustering in evolutionary algorithms to efficiently compute simultaneously local and global minima.Dimitris K. Tasoulis, Vassilis P. Plagianakos, Michael N. Vrahatis
2005IJCNNSpiking neural network training using evolutionary algorithms.Nicos G. Pavlidis, O. K. Tasoulis, Vassilis P. Plagianakos, George Nikiforidis, Michael N. Vrahatis
2005IJCNNComputational intelligence techniques for acute leukemia gene expression data classification.Vassilis P. Plagianakos, Dimitris K. Tasoulis, Michael N. Vrahatis
2004CECVector evaluated differential evolution for multiobjective optimization.Konstantinos E. Parsopoulos, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis
2004CECParallel differential evolution.Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis
2004ICAISCOnline Neural Network Training for Automatic Ischemia Episode Detection.Dimitris K. Tasoulis, Liviu Vladutu, Vassilis P. Plagianakos, Anastasios Bezerianos, Michael N. Vrahatis
2000IJCNNDevelopment and Convergence Analysis of Training Algorithms with Local Learning Rate Adaptation.George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis
2000IJCNNTraining Neural Networks with Threshold Activation Functions and Constrained Integer Weights.Vassilis P. Plagianakos, Michael N. Vrahatis
1999CECNeural network training with constrained integer weights.Vassilis P. Plagianakos, Michael N. Vrahatis
1999IJCNNSign-methods for training with imprecise error function and gradient values.George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis
1999IJCNNConvergence analysis of the Quickprop method.Michael N. Vrahatis, George D. Magoulas, Vassilis P. Plagianakos