A. Likas

发表

A kurtosis-based dynamic approach to Gaussian mixture modeling

Nikos A. Vlassis, Aristidis Likas, N. Vlassis, 1999, IEEE Trans. Syst. Man Cybern. Part A.

Artificial neural network methods in quantum mechanics

D. Fotiadis, A. Likas, I. Lagaris, 1997, quant-ph/9705029.

Bayesian feature and model selection for Gaussian mixture models

Aristidis Likas, Constantinos Constantinopoulos, Michalis K. Titsias, 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Kernel-Based Weighted Multi-view Clustering

Aristidis Likas, Grigorios Tzortzis, A. Likas, 2012, 2012 IEEE 12th International Conference on Data Mining.

Combination of high-resolution magic angle spinning proton magnetic resonance spectroscopy and microscale genomics to type brain tumor biopsies.

L. Astrakas, K. Blekas, Jiangwen Zhang, 2007, International journal of molecular medicine.

Integrating particle swarm optimization with reinforcement learning in noisy problems

Chrysostomos D. Stylios, George K. Georgoulas, Aristidis Likas, 2012, GECCO '12.

A Reinforcement Learning Approach to On-line Clustering

Aristidis Likas, A. Likas, 1999 .

Life After the EM Algorithm : The Variational Approximation for Bayesian Inference .

Senior Member, A. Likas, D. Tzikas, 2008 .

A split-and-merge framework for 2D shape summarization

A. Likas, Christophoros Nikou, Demetrios Gerogiannis, 2011, 2011 7th International Symposium on Image and Signal Processing and Analysis (ISPA).

A TUTORIAL ON RELEVANCE VECTOR MACHINES FOR REGRESSION AND CLASSIFICATION WITH APPLICATIONS

N. Galatsanos, A. Likas, Liyang Wei, 2006 .

Relevance feedback approach for image retrieval combining support vector machines and adapted Gaussian mixture models

A. Likas, N. Galatsanos, A. Stafylopatis, 2011, IET Image Processing.

Probability density estimation using artificial neural networks

A. Likas, 2001 .

Electrocardiogram (ECG): Automated Diagnosis

A. Likas, L. Michalis, D. Fotiadis, 2006 .

Combining magnetic resonance spectroscopy and molecular genomics offers better accuracy in brain tumor typing and prediction of survival than either methodology alone.

L. Astrakas, K. Blekas, M. Mindrinos, 2011, International journal of oncology.

A knowledge-based technique for automated detection of ischaemic episodes in long duration electrocardiograms

C. Papaloukas, A. P. Liavas, D. Fotiadis, 2006, Medical and Biological Engineering and Computing.

Automated methods for ischemia detection in long-duration ECGs

Dimitrios I. Fotiadis, Aristidis Likas, Costas Papaloukas, 2003 .

Use of a novel rule-based expert system in the detection of changes in the ST segment and the T wave in long duration ECGs.

Dimitrios I Fotiadis, Aristidis Likas, Costas Papaloukas, 2002, Journal of electrocardiology.

Kernel Methods for Functional Neuroimaging Analysis

S. Strother, Fuqiang Zhao, N. Galatsanos, 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

BAYESIAN RESTORATION USING A NEW HIERARCHICAL DIRECTIONAL CONTINUOUS EDGE IMAGE PRIOR By

Aristidis Likas, Nikolaos Galatsanos, Giannis Chantas, 2005 .

A fuzzy neural network approach to classification based on proximity characteristics of patterns

Andreas Stafylopatis, Konstantinos Blekas, Aristidis Likas, 1997, Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence.

Mining Clinical Data

Argyris Kalogeratos, Aristidis Likas, Z. Babovic, 2013 .

Piecewise continuous approximation of two – dimensional functions using neural networks

A. Likas, I. Lagaris, I. Tsoulos, 2022 .

Artiicial Neural Networks for Solving Ordinary and Partial Diierential Equations

D. Fotiadis, A. Likas, I. Lagaris, 1998 .

Childcares an intelligent collaborative environment for out-of-hospital child healthcare

Dimitrios I. Fotiadis, Aristidis Likas, D. Fotiadis, 2002 .

Bayesian Methods Based on Variational Approximations for Blind Image Deconvolution

Nikolas P. Galatsanos, Aristidis Likas, N. Galatsanos, 2007 .

Scanning X-ray Fluorescence Data Analysis for the Identification of Byzantine Icons’ Materials, Techniques, and State of Preservation: A Case Study

Giannis K. Chantas, A. Likas, D. Anagnostopoulos, 2022, J. Imaging.

A Hybrid Neural Optimization Scheme Based onParallel

A. Likas, A. Stafylopatis, UpdatesG. Papageorgiou, 1997 .

ates and Multiscaling: An Efficient Neural etwork Approach to Combinatorial Optimization

A. Likas, A. Stafylopatis, 1996 .

The "Citation" Platform: Semantics-Based Modeling & Retrieval of Administrative Information

Dimitrios I. Fotiadis, Aristidis Likas, A. G. Anagnostakis, 2002, ICWI.

A real-time monitoring platform for assessing rehabilitation of the lower extremities in athletes

Dimitrios I. Fotiadis, Aristidis Likas, Constantine Glaros, 2003 .

OP-CBIO160301 2710..2712

Michalis D. Mantzaris, Tahsin F. Kellici, A. Likas, 2016 .

Transformer-Based Music Language Modelling and Transcription

A. Likas, John Pavlopoulos, Christos Zonios, 2022, Proceedings of the 12th Hellenic Conference on Artificial Intelligence.

A convolutional neural network based system for detection of actinic keratosis in clinical images of cutaneous field cancerization

A. Likas, P. Spyridonos, I. Bassukas, 2023, Biomed. Signal Process. Control..

Sparse regression mixture modeling with the multi-kernel relevance vector machine

K. Blekas, A. Likas, 2014, Knowledge and Information Systems.

Global k-means++: an effective relaxation of the global k-means clustering algorithm

A. Likas, G. Vardakas, 2022, ArXiv.

Editorial

Dimitrios Kalles, Konstantinos Blekas, Aristidis Likas, 2015, Int. J. Artif. Intell. Tools.

A GREEDY METHOD FOR MIXTURE-BASED CLASSIFICATION

Aristidis Likas, Constantinos Constantinopoulos, A. Likas, 2004 .

Embedding knowledge into stochastic learning automata for fast solution of binary constraint satisfaction problems

Andreas Stafylopatis, Aristidis Likas, D. Kontoravdis, 1993, ESANN.

Collision-Free Movement of an Autonomous Vehicle Using Reinforcement Learning

Andreas Stafylopatis, Andreas Stafylopatis, Aristidis Likas, 1992, ECAI.

A Bayesian Framework for Image Segmentation With Spatially Varying Mixtures

Nikolas P. Galatsanos, Aristidis Likas, Christophoros Nikou, 2010, IEEE Transactions on Image Processing.

A Class-Adaptive Spatially Variant Mixture Model for Image Segmentation

Nikolas P. Galatsanos, Aristidis Likas, Christophoros Nikou, 2007, IEEE Transactions on Image Processing.

A spatially constrained mixture model for image segmentation

Nikolas P. Galatsanos, Isaac E. Lagaris, Konstantinos Blekas, 2005, IEEE Transactions on Neural Networks.

The MinMax k-Means clustering algorithm

Aristidis Likas, Grigorios Tzortzis, A. Likas, 2014, Pattern Recognit..

The global k-means clustering algorithm

Nikos A. Vlassis, Aristidis Likas, Jakob J. Verbeek, 2003, Pattern Recognit..

Bayesian regression of functional neuroimages

Nikolas P. Galatsanos, Miles N. Wernick, Aristidis Likas, 2004, 2004 12th European Signal Processing Conference.

A variational approach for Bayesian blind image deconvolution

Nikolas P. Galatsanos, Aristidis Likas, N. Galatsanos, 2004, IEEE Transactions on Signal Processing.

Fully Unsupervised M-FISH Chromosome Image Characterization

Aristidis Likas, Petros S. Karvelis, A. Likas, 2013, IEEE Journal of Biomedical and Health Informatics.

The Mixture of Multi-kernel Relevance Vector Machines Model

Konstantinos Blekas, Aristidis Likas, K. Blekas, 2012, 2012 IEEE 12th International Conference on Data Mining.

A Sparse Regression Mixture Model for Clustering Time-Series

Nikolas P. Galatsanos, Konstantinos Blekas, Aristidis Likas, 2008, SETN.

Image segmentation with a class-adaptive spatially constrained mixture model

Nikolas P. Galatsanos, Konstantinos Blekas, Aristidis Likas, 2006, 2006 14th European Signal Processing Conference.

An incremental training method for the probabilistic RBF network

Aristidis Likas, Constantinos Constantinopoulos, A. Likas, 2006, IEEE Trans. Neural Networks.

Motif-Based Protein Sequence Classification Using Neural Networks

Dimitrios I. Fotiadis, Konstantinos Blekas, Aristidis Likas, 2005, J. Comput. Biol..

A Greedy EM Algorithm for Gaussian Mixture Learning

Nikos A. Vlassis, Aristidis Likas, N. Vlassis, 2002, Neural Processing Letters.

Shared kernel models for class conditional density estimation

Aristidis Likas, Michalis K. Titsias, M. Titsias, 2001, IEEE Trans. Neural Networks.

The variational approximation for Bayesian inference

D.G. Tzikas, A.C. Likas, N.P. Galatsanos, 2008, IEEE Signal Processing Magazine.

Distance from Unimodality for the Assessment of Opinion Polarization

A. Likas, John Pavlopoulos, 2022, Cognitive computation.

An ultrasound wearable system for the monitoring and acceleration of fracture healing in long bones

Dimitrios I. Fotiadis, Aristidis Likas, Vasilios C. Protopappas, 2005, IEEE Transactions on Biomedical Engineering.

Bayesian Kernel Methods for Analysis of Functional Neuroimages

Xu Chen, Nikolas P. Galatsanos, Yongyi Yang, 2007, IEEE Transactions on Medical Imaging.

The UU-test for Statistical Modeling of Unimodal Data

Aristidis Likas, Paraskevi Chasani, A. Likas, 2020, Pattern Recognit..

The Projected Dip-means Clustering Algorithm

Aristidis Likas, Theofilos Chamalis, A. Likas, 2018, SETN.

Dip-means: an incremental clustering method for estimating the number of clusters

Argyris Kalogeratos, Aristidis Likas, A. Likas, 2012, NIPS.

Discrete optimisation based on the combined use of reinforcement and constraint satisfaction schemes

Andreas Stafylopatis, Aristidis Likas, D. Kontoravdis, 1995, Neural Computing & Applications.

A Reinforcement Learning Approach to Online Clustering

Aristidis Likas, A. Likas, 1999, Neural Computation.

Parallel Recombinative Reinforcement Learning: A Genetic Approach

Andreas Stafylopatis, Konstantinos Blekas, Aristidis Likas, 1996 .

Parallel Recombinative Reinforcement Learning (Extended Abstract)

Andreas Stafylopatis, Konstantinos Blekas, Aristidis Likas, 1995, ECML.

Enhancing Stochasticity in Reinforcement Learning Schemes: Application to the Exploration of Binary Domains

Andreas Stafylopatis, Aristidis Likas, D. Kontoravdis, 1995 .

Mixture of Experts Classification Using a Hierarchical Mixture Model

Aristidis Likas, Michalis K. Titsias, M. Titsias, 2002, Neural Computation.

Automatic discrimination of actinic keratoses from clinical photographs

Panagiota Spyridonos, Aristidis Likas, Georgios Gaitanis, 2017, Comput. Biol. Medicine.

Artificial neural networks for solving ordinary and partial differential equations

Dimitrios I. Fotiadis, Isaac E. Lagaris, Aristidis Likas, 1997, IEEE Trans. Neural Networks.

Variational Bayesian Image Restoration Based on a Product of $t$-Distributions Image Prior

Nikolas P. Galatsanos, Michael A. Saunders, Giannis K. Chantas, 2008, IEEE Transactions on Image Processing.

Bayesian Restoration Using a New Nonstationary Edge-Preserving Image Prior

Nikolas P. Galatsanos, Giannis K. Chantas, Aristidis Likas, 2006, IEEE Transactions on Image Processing.

Neural-network methods for boundary value problems with irregular boundaries

Dimitris G. Papageorgiou, Isaac E. Lagaris, Aristidis Likas, 2000, IEEE Trans. Neural Networks Learn. Syst..

An Analytic Distance Metric for Gaussian Mixture Models with Application in Image Retrieval

Nikolas P. Galatsanos, Aristidis Likas, Giorgos Sfikas, 2005, ICANN.

Semi-supervised and active learning with the probabilistic RBF classifier

Aristidis Likas, Constantinos Constantinopoulos, A. Likas, 2008, Neurocomputing.

Class Conditional Density Estimation Using Mixtures with Constrained Component Sharing

Aristidis Likas, Michalis K. Titsias, M. Titsias, 2003, IEEE Trans. Pattern Anal. Mach. Intell..

Text document clustering using global term context vectors

Argyris Kalogeratos, Aristidis Likas, A. Likas, 2011, Knowledge and Information Systems.

An Efficient Method for Explaining the Decisions of the Probabilistic RBF Classification Network

Aristidis Likas, Igor Kononenko, Constantinos Constantinopoulos, 2007 .

Greedy mixture learning for multiple motif discovery in biological sequences

Dimitrios I. Fotiadis, Konstantinos Blekas, Aristidis Likas, 2003, Bioinform..

A Connectionist Approach for Solving Large Constraint Satisfaction Problems

George Papageorgiou, Andreas Stafylopatis, Aristidis Likas, 1997, Applied Intelligence.

Clinical Decision Support Systems

Yorgos Goletsis, Aristidis Likas, Athanassios Papadopoulos, 2006 .

Automated ischemic beat classification using genetic algorithms and multicriteria decision analysis

Yorgos Goletsis, Dimitrios I. Fotiadis, Lampros K. Michalis, 2004, IEEE Transactions on Biomedical Engineering.

Convex Mixture Models for Multi-view Clustering

Aristidis Likas, Grigorios Tzortzis, A. Likas, 2009, ICANN.

Visual Tracking by Weighted Likelihood Maximization

Aristidis Likas, Christophoros Nikou, Vasileios Karavasilis, 2012, 2012 IEEE 24th International Conference on Tools with Artificial Intelligence.

Engineering Applications of Neural Networks

Aristidis Likas, A. Likas, 2017, Communications in Computer and Information Science.

Scene Detection in Videos Using Shot Clustering and Sequence Alignment

Nikolas P. Galatsanos, Aristidis Likas, Vasileios Chasanis, 2009, IEEE Transactions on Multimedia.

A Support Vector Machine Approach for Video Shot Detection

Nikolas P. Galatsanos, Aristidis Likas, Vasileios Chasanis, 2008, New Directions in Intelligent Interactive Multimedia.

Real time visual tracking using a spatially weighted von Mises mixture model

Aristidis Likas, Christophoros Nikou, Vasileios Karavasilis, 2017, Pattern Recognit. Lett..

Visual tracking using spatially weighted likelihood of Gaussian mixtures

Aristidis Likas, Christophoros Nikou, Vasileios Karavasilis, 2015, Comput. Vis. Image Underst..

Visual tracking using the Earth Mover's Distance between Gaussian mixtures and Kalman filtering

Aristidis Likas, Christophoros Nikou, Vasileios Karavasilis, 2011, Image Vis. Comput..

The global kernel k-means clustering algorithm

Aristidis Likas, Grigorios Tzortzis, A. Likas, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

A note on a new greedy-solution representation and a new greedy parallelizable heuristic for the traveling salesman problem☆

Vangelis Th. Paschos, Aristidis Likas, A. Likas, 2002 .

Deep Belief Networks for Spam Filtering

Aristidis Likas, Grigorios Tzortzis, A. Likas, 2007, 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007).

Semantics-based information modeling for the health-care administration sector: the Citation platform

Dimitrios I. Fotiadis, Aristidis Likas, A. G. Anagnostakis, 2005, IEEE Transactions on Information Technology in Biomedicine.

A clustering method based on boosting

Andreas Stafylopatis, Aristidis Likas, Dimitrios S. Frossyniotis, 2004, Pattern Recognit. Lett..

Simultaneous detection of abrupt cuts and dissolves in videos using support vector machines

Nikolas P. Galatsanos, Aristidis Likas, Vasileios Chasanis, 2009, Pattern Recognit. Lett..

Unsupervised Learning of Gaussian Mixtures Based on Variational Component Splitting

Aristidis Likas, Constantinos Constantinopoulos, A. Likas, 2007, IEEE Transactions on Neural Networks.

Modeling sets of unordered points using highly eccentric ellipses

A. Likas, Christophoros Nikou, Demetrios Gerogiannis, 2014, EURASIP J. Adv. Signal Process..

Efficiently Explaining Decisions of Probabilistic RBF Classification Networks

Erik Strumbelj, Aristidis Likas, Marko Robnik-Sikonja, 2011, ICANNGA.

A divide-and-conquer method for multi-net classifiers

Andreas Stafylopatis, Aristidis Likas, Dimitrios Frosyniotis, 2003, Pattern Analysis & Applications.

The Global Kernel $k$-Means Algorithm for Clustering in Feature Space

Aristidis Likas, Grigorios Tzortzis, A. Likas, 2009, IEEE Transactions on Neural Networks.

Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machines

Dimitrios I. Fotiadis, Aristidis Likas, Athanasios N. Papadopoulos, 2005, Artif. Intell. Medicine.

Late fusion of deep and shallow features to improve discrimination of actinic keratosis from normal skin using clinical photography

Panagiota Spyridonos, Aristidis Likas, Georgios Gaitanis, 2019, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.

Cytological Diagnosis Based on Fuzzy Neural Networks

D. Kontoravdis,, A. Likas,, P. Krakitsos,, 1998 .

Elimination of Outliers from 2-D Point Sets Using the Helmholtz Principle

Aristidis Likas, Christophoros Nikou, Demetrios Gerogiannis, 2015, IEEE Signal Processing Letters.

A Set Membership Approach to Discovering Feature Relevance and Explaining Neural Classifier Decisions

A. Likas, S. P. Adam, 2022, ArXiv.

Neural Splines: Exploiting Parallelism for Fuction Approximation Using Modular Neural Networks

Isaac E. Lagaris, Aristidis Likas, Ioannis G. Tsoulos, 2005, Neural Parallel Sci. Comput..

Solving differential equations with neural networks: implementation on a DSP platform

Isaac E. Lagaris, Aristidis Likas, K. Valasoulis, 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).

Piecewise Neural Networks for Function Approximation, Cast in a Form Suitable for Parallel Computation

Isaac E. Lagaris, Aristidis Likas, Ioannis G. Tsoulos, 2002, SETN.

Neural Network Methods for Boundary Value Problems Defined in Arbitrarily Shaped Domains

Dimitris G. Papageorgiou, Isaac E. Lagaris, Aristidis Likas, 1998, ArXiv.

Neural clustering based on implicit maximum likelihood

A. Likas, Georgios Vardakas, 2023, Neural Computing and Applications.

Relevance Feedback for Content-Based Image Retrieval Using Support Vector Machines and Feature Selection

Nikolas P. Galatsanos, Andreas Stafylopatis, Aristidis Likas, 2009, ICANN.

Document clustering using synthetic cluster prototypes

Argyris Kalogeratos, Aristidis Likas, A. Likas, 2011, Data Knowl. Eng..

Object Detection and Navigation of a Mobile Robot by Fusing Laser and Camera Information

A. Likas, K. Vlachos, Spyridon Syntakas, 2022, 2022 30th Mediterranean Conference on Control and Automation (MED).

Artificial Intelligence: Methods and Applications

Konstantinos Blekas, Aristidis Likas, Dimitris Kalles, 2014, Lecture Notes in Computer Science.

Training the random neural network using quasi-Newton methods

Andreas Stafylopatis, Aristidis Likas, A. Likas, 2000, Eur. J. Oper. Res..

Multiple View Clustering Using a Weighted Combination of Exemplar-Based Mixture Models

Grigorios Tzortzis, C. L. Likas, A. Likas, 2010, IEEE Transactions on Neural Networks.

Variational Bayesian Sparse Kernel-Based Blind Image Deconvolution With Student's-t Priors

Nikolas P. Galatsanos, Aristidis Likas, Dimitris Tzikas, 2009, IEEE Transactions on Image Processing.

Probabilistic relevance feedback approach for content-based image retrieval based on gaussian mixture models

Nikolas P. Galatsanos, Andreas Stafylopatis, Aristidis Likas, 2009, IET Image Process..

Probabilistic Models Based on the Pi-Sigmoid Distribution

Aristidis Likas, Anastasios Alivanoglou, A. Likas, 2008, ANNPR.

Robust Image Registration using Mixtures of t-distributions

Aristidis Likas, Christophoros Nikou, Demetrios Gerogiannis, 2007, 2007 IEEE 11th International Conference on Computer Vision.

Rigid Image Registration based on Pixel Grouping

Aristidis Likas, Christophoros Nikou, Demetrios Gerogiannis, 2007, 14th International Conference on Image Analysis and Processing (ICIAP 2007).

Active Learning with the Probabilistic RBF Classifier

Aristidis Likas, Constantinos Constantinopoulos, A. Likas, 2006, ICANN.

A Relevance Feedback Approach for Content Based Image Retrieval Using Gaussian Mixture Models

Nikolas P. Galatsanos, Andreas Stafylopatis, Aristidis Likas, 2006, ICANN.

Efficient Training Algorithms for the Probabilistic RBF Network

Aristidis Likas, Constantinos Constantinopoulos, A. Likas, 2004, SETN.

A Bayesian Regularization Method for the Probabilistic RBF Network

Aristidis Likas, Constantinos Constantinopoulos, Michalis K. Titsias, 2002, SETN.

An automatic microcalcification detection system based on a hybrid neural network classifier

Dimitrios I. Fotiadis, Aristidis Likas, Athanasios N. Papadopoulos, 2002, Artif. Intell. Medicine.

A novel method for automated EMG decomposition and MUAP classification

Christos D. Katsis, Yorgos Goletsis, Dimitrios I. Fotiadis, 2006, Artif. Intell. Medicine.

Intelligent Patient Monitoring

Aristidis Likas, Vasilios C. Protopappas, V. Protopappas, 2006 .

Training Reinforcement Neurocontrollers Using the Polytope Algorithm

Isaac E. Lagaris, Aristidis Likas, A. Likas, 1998, Neural Processing Letters.

Under Consideration for Publication in Knowledge and Information Systems Sparse Regression Mixture Modeling with the Multi-kernel Relevance Vector Machine

Konstantinos Blekas, Aristidis Likas, K. Blekas, 2022 .

PRESS: PRotEin S-Sulfenylation server

Aristidis Likas, Grigorios Tzortzis, Michalis D. Mantzaris, 2016, Bioinform..

Group updates and multiscaling: an efficient neural network approach to combinatorial optimization

Andreas Stafylopatis, Aristidis Likas, A. Likas, 1996, IEEE Trans. Syst. Man Cybern. Part B.

Transductive Reliability Estimation for Kernel Based Classifiers

Aristidis Likas, Dimitris Tzikas, Matjaz Kukar, 2007, IDA.

Modeling sets of unordered points using highly eccentric ellipses

Aristidis Likas, Christophoros Nikou, Demetrios Gerogiannis, 2014, EURASIP Journal on Advances in Signal Processing.

Image Modeling and Segmentation Using Incremental Bayesian Mixture Models

Aristidis Likas, Constantinos Constantinopoulos, A. Likas, 2007, CAIP.

Registering sets of points using Bayesian regression

Aristidis Likas, Christophoros Nikou, Demetrios Gerogiannis, 2012, Neurocomputing.

A Parallel Algorithm for the Minimum Weighted Vertex Cover Problem

Andreas Stafylopatis, Aristidis Likas, A. Likas, 1995, Inf. Process. Lett..

The Inclusion Measure for Community Evaluation and Detection in Unweighted Networks

Aristidis Likas, Nikolaos Koufos, A. Likas, 2018, 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

A robust knowledge-based technique for ischemia detection in noisy ECGs

A. Likas, C. Papaloukas, D.I. Fotiadis, 2000, KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516).

Efficient Video Shot Summarization Using an Enhanced Spectral Clustering Approach

Nikolas P. Galatsanos, Aristidis Likas, Vasileios Chasanis, 2008, ICANN.

Mixture model analysis of DNA microarray images

Nikolas P. Galatsanos, Isaac E. Lagaris, Konstantinos Blekas, 2005, IEEE Transactions on Medical Imaging.

Distance from Unimodality for the Assessment of Opinion Polarization

A. Likas, John Pavlopoulos, 2022, Cognitive Computation.

An ischemia detection method based on artificial neural networks

Dimitrios I. Fotiadis, Lampros K. Michalis, Aristidis Likas, 2002, Artif. Intell. Medicine.

Incremental Mixture Learning for Clustering Discrete Data

Konstantinos Blekas, Aristidis Likas, K. Blekas, 2004, SETN.

Motif-Based Protein Sequence Classification Using Neural Networks

K. Blekas, A. Likas, D. I. Fotiadis, 2005, J. Comput. Biol..

A wearable intelligent system for monitoring health condition and rehabilitation of running athletes

Aristidis Likas, D. I. Fotiadis, Constantine Glaros, 2003, 4th International IEEE EMBS Special Topic Conference on Information Technology Applications in Biomedicine, 2003..