| 2009 |
|---|
| 74 | EE | Dimitris Tzikas,
Aristidis Likas,
Nikolas P. Galatsanos:
Variational Bayesian Sparse Kernel-Based Blind Image Deconvolution With Student's-t Priors.
IEEE Transactions on Image Processing 18(4): 753-764 (2009) |
| 73 | EE | Vasileios Chasanis,
Aristidis Likas,
Nikolas P. Galatsanos:
Simultaneous detection of abrupt cuts and dissolves in videos using support vector machines.
Pattern Recognition Letters 30(1): 55-65 (2009) |
| 2008 |
|---|
| 72 | EE | Anastasios Alivanoglou,
Aristidis Likas:
Probabilistic Models Based on the Pi-Sigmoid Distribution.
ANNPR 2008: 36-43 |
| 71 | EE | Vasileios Chasanis,
Aristidis Likas,
Nikolas P. Galatsanos:
Efficient Video Shot Summarization Using an Enhanced Spectral Clustering Approach.
ICANN (1) 2008: 847-856 |
| 70 | EE | Apostolos Marakakis,
Nikolas P. Galatsanos,
Aristidis Likas,
Andreas Stafylopatis:
Application of Relevance Feedback in Content Based Image Retrieval Using Gaussian Mixture Models.
ICTAI (1) 2008: 141-148 |
| 69 | EE | Grigorios Tzortzis,
Aristidis Likas:
The global kernel k-means clustering algorithm.
IJCNN 2008: 1977-1984 |
| 68 | EE | Dimitris Tzikas,
Aristidis Likas,
Nikolas P. Galatsanos:
Incremental Relevance Vector Machine with Kernel Learning.
SETN 2008: 301-312 |
| 67 | EE | Konstantinos Blekas,
Nikolas P. Galatsanos,
Aristidis Likas:
A Sparse Regression Mixture Model for Clustering Time-Series.
SETN 2008: 64-72 |
| 66 | EE | Vasileios Chasanis,
Aristidis Likas,
Nikolas P. Galatsanos:
Video rushes summarization using spectral clustering and sequence alignment.
TVS 2008: 75-79 |
| 65 | EE | Vasileios Chasanis,
Aristidis Likas,
Nikolas P. Galatsanos:
A Support Vector Machine Approach for Video Shot Detection.
New Directions in Intelligent Interactive Multimedia 2008: 45-54 |
| 64 | EE | Giannis K. Chantas,
Nikolas P. Galatsanos,
Aristidis Likas,
Michael Saunders:
Variational Bayesian Image Restoration Based on a Product of t-Distributions Image Prior.
IEEE Transactions on Image Processing 17(10): 1795-1805 (2008) |
| 2007 |
|---|
| 63 | EE | Constantinos Constantinopoulos,
Aristidis Likas:
Image Modeling and Segmentation Using Incremental Bayesian Mixture Models.
CAIP 2007: 596-603 |
| 62 | EE | Demetrios Gerogiannis,
Christophoros Nikou,
Aristidis Likas:
Robust Image Registration using Mixtures of t-distributions.
ICCV 2007: 1-8 |
| 61 | EE | Demetrios Gerogiannis,
Christophoros Nikou,
Aristidis Likas:
Rigid Image Registration based on Pixel Grouping.
ICIAP 2007: 595-602 |
| 60 | EE | Dimitris Tzikas,
Aristidis Likas,
Nikolas P. Galatsanos:
Variational Bayesian Blind Image Deconvolution with Student-T Priors.
ICIP (1) 2007: 109-112 |
| 59 | EE | Grigorios Tzortzis,
Aristidis Likas:
Deep Belief Networks for Spam Filtering.
ICTAI (2) 2007: 306-309 |
| 58 | EE | Dimitris Tzikas,
Matjaz Kukar,
Aristidis Likas:
Transductive Reliability Estimation for Kernel Based Classifiers.
IDA 2007: 37-47 |
| 57 | | Dimitris Tzikas,
Aristidis Likas,
Nikolas P. Galatsanos:
Robust variational bayesian kernel based blind image deconvolution.
VISAPP (Special Sessions) 2007: 143-150 |
| 56 | EE | Ana S. Lukic,
Miles N. Wernick,
Dimitris Tzikas,
X. Chen,
Aristidis Likas,
Nikolas P. Galatsanos,
Yongyi Yang,
E. Zhao,
Stephen C. Strother:
Bayesian Kernel Methods for Analysis of Functional Neuroimages.
IEEE Trans. Med. Imaging 26(12): 1613-1624 (2007) |
| 55 | EE | Christophoros Nikou,
Nikolas P. Galatsanos,
Aristidis Likas:
A Class-Adaptive Spatially Variant Mixture Model for Image Segmentation.
IEEE Transactions on Image Processing 16(4): 1121-1130 (2007) |
| 54 | EE | Constantinos Constantinopoulos,
Aristidis Likas:
Unsupervised Learning of Gaussian Mixtures Based on Variational Component Splitting.
IEEE Transactions on Neural Networks 18(3): 745-755 (2007) |
| 53 | EE | Dimitris Tzikas,
Aristidis Likas,
Nikolas P. Galatsanos:
Large Scale Multikernel Relevance Vector Machine for Object Detection.
International Journal on Artificial Intelligence Tools 16(6): 967-979 (2007) |
| 2006 |
|---|
| 52 | EE | Constantinos Constantinopoulos,
Aristidis Likas:
Active Learning with the Probabilistic RBF Classifier.
ICANN (1) 2006: 357-366 |
| 51 | EE | Apostolos Marakakis,
Nikolas P. Galatsanos,
Aristidis Likas,
Andreas Stafylopatis:
A Relevance Feedback Approach for Content Based Image Retrieval Using Gaussian Mixture Models.
ICANN (2) 2006: 84-93 |
| 50 | EE | Dimitris Tzikas,
Aristidis Likas,
Nikolas P. Galatsanos:
Large Scale Multikernel RVM for Object Detection.
SETN 2006: 389-399 |
| 49 | EE | Argyris Kalogeratos,
Aristidis Likas:
A Significance-Based Graph Model for Clustering Web Documents.
SETN 2006: 516-519 |
| 48 | EE | C. D. Katsis,
Yorgos Goletsis,
Aristidis Likas,
Dimitrios I. Fotiadis,
I. Sarmas:
A novel method for automated EMG decomposition and MUAP classification.
Artificial Intelligence in Medicine 37(1): 55-64 (2006) |
| 47 | EE | Constantinos Constantinopoulos,
Michalis K. Titsias,
Aristidis Likas:
Bayesian Feature and Model Selection for Gaussian Mixture Models.
IEEE Trans. Pattern Anal. Mach. Intell. 28(6): 1013-1018 (2006) |
| 46 | EE | Giannis K. Chantas,
Nikolas P. Galatsanos,
Aristidis Likas:
Bayesian Restoration Using a New Nonstationary Edge-Preserving Image Prior.
IEEE Transactions on Image Processing 15(10): 2987-2997 (2006) |
| 45 | EE | Constantinos Constantinopoulos,
Aristidis Likas:
An incremental training method for the probabilistic RBF network.
IEEE Transactions on Neural Networks 17(4): 966-974 (2006) |
| 2005 |
|---|
| 44 | EE | Giorgos Sfikas,
Constantinos Constantinopoulos,
Aristidis Likas,
Nikolas P. Galatsanos:
An Analytic Distance Metric for Gaussian Mixture Models with Application in Image Retrieval.
ICANN (2) 2005: 835-840 |
| 43 | EE | John Chantas,
Nikolas P. Galatsanos,
Aristidis Likas:
Maximum a posteriori image restoration based on a new directional continuous edge image prior.
ICIP (1) 2005: 941-944 |
| 42 | EE | Athanasios Papadopoulos,
Dimitrios I. Fotiadis,
Aristidis Likas:
Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machines.
Artificial Intelligence in Medicine 34(2): 141-150 (2005) |
| 41 | EE | Konstantinos Blekas,
Nikolas P. Galatsanos,
Aristidis Likas,
Isaac E. Lagaris:
Mixture model analysis of DNA microarray images.
IEEE Trans. Med. Imaging 24(7): 901-909 (2005) |
| 40 | EE | A. G. Anagnostakis,
M. Tzima,
G. C. Sakellaris,
Dimitrios I. Fotiadis,
Aristidis Likas:
Semantics-based information modeling for the health-care administration sector: the Citation platform.
IEEE Transactions on Information Technology in Biomedicine 9(2): 239-247 (2005) |
| 39 | EE | Konstantinos Blekas,
Dimitrios I. Fotiadis,
Aristidis Likas:
Motif-Based Protein Sequence Classification Using Neural Networks.
Journal of Computational Biology 12(1): 64-82 (2005) |
| 2004 |
|---|
| 38 | EE | Konstantinos Valasoulis,
Aristidis Likas:
Probabilistic Shape-Based Image Indexing and Retrieval.
ICPR (2) 2004: 969-972 |
| 37 | EE | Giannis K. Chantas,
Nikolas P. Galatsanos,
Aristidis Likas:
Non Stationary Bayesian Image Restoration.
ICPR (4) 2004: 689-692 |
| 36 | | Dimitris Tzikas,
Aristidis Likas,
Nikolas P. Galatsanos,
Ana S. Lukic,
Miles N. Wernick:
Relevance Vector Machine Analysis of Functional Neuroimages.
ISBI 2004: 1004-1007 |
| 35 | EE | Constantinos Constantinopoulos,
Aristidis Likas:
Efficient Training Algorithms for the Probabilistic RBF Network.
SETN 2004: 183-190 |
| 34 | EE | Konstantinos Blekas,
Aristidis Likas:
Incremental Mixture Learning for Clustering Discrete Data.
SETN 2004: 210-219 |
| 33 | EE | Dimitrios S. Frossyniotis,
Aristidis Likas,
Andreas Stafylopatis:
A clustering method based on boosting.
Pattern Recognition Letters 25(6): 641-654 (2004) |
| 2003 |
|---|
| 32 | EE | Konstantinos Blekas,
Dimitrios I. Fotiadis,
Aristidis Likas:
Protein Sequence Classification Using Probabilistic Motifs and Neural Networks.
ICANN 2003: 702-709 |
| 31 | | Aristidis Likas,
Nikolas P. Galatsanos:
A variational method for Bayesian blind image deconvolution.
ICIP (2) 2003: 973-976 |
| 30 | | Konstantinos Blekas,
Dimitrios I. Fotiadis,
Aristidis Likas:
Greedy mixture learning for multiple motif discovery in biological sequences.
Bioinformatics 19(5): 607-617 (2003) |
| 29 | EE | Michalis K. Titsias,
Aristidis Likas:
Class Conditional Density Estimation Using Mixtures with Constrained Component Sharing.
IEEE Trans. Pattern Anal. Mach. Intell. 25(7): 924-928 (2003) |
| 28 | EE | Dimitrios Frosyniotis,
Andreas Stafylopatis,
Aristidis Likas:
A divide-and-conquer method for multi-net classifiers.
Pattern Anal. Appl. 6(1): 32-40 (2003) |
| 27 | EE | Aristidis Likas,
Nikos A. Vlassis,
Jakob J. Verbeek:
The global k-means clustering algorithm.
Pattern Recognition 36(2): 451-461 (2003) |
| 2002 |
|---|
| 26 | EE | A. G. Anagnostakis,
G. C. Sakellaris,
M. Tzima,
Dimitrios I. Fotiadis,
Aristidis Likas:
CITATION - Citizen Information Tool in Smart Administration.
EGOV 2002: 307-312 |
| 25 | | A. G. Anagnostakis,
G. C. Sakellaris,
M. Tzima,
Dimitrios I. Fotiadis,
Aristidis Likas:
The "Citation" Platform: Semantics-Based Modeling & Retrieval of Administrative Information.
ICWI 2002: 577-583 |
| 24 | EE | Ioannis G. Tsoulos,
Isaac E. Lagaris,
Aristidis Likas:
Piecewise Neural Networks for Function Approximation, Cast in a Form Suitable for Parallel Computation.
SETN 2002: 314-324 |
| 23 | EE | Constantinos Constantinopoulos,
Michalis K. Titsias,
Aristidis Likas:
A Bayesian Regularization Method for the Probabilistic RBF Network.
SETN 2002: 337-345 |
| 22 | | Costas Papaloukas,
Dimitrios I. Fotiadis,
Aristidis Likas,
Lampros K. Michalis:
An ischemia detection method based on artificial neural networks.
Artificial Intelligence in Medicine 24(2): 167-178 (2002) |
| 21 | | Athanasios Papadopoulos,
Dimitrios I. Fotiadis,
Aristidis Likas:
An automatic microcalcification detection system based on a hybrid neural network classifier.
Artificial Intelligence in Medicine 25(2): 149-167 (2002) |
| 20 | EE | Michalis K. Titsias,
Aristidis Likas:
Mixture of Experts Classification Using a Hierarchical Mixture Model.
Neural Computation 14(9): 2221-2244 (2002) |
| 19 | | Nikos A. Vlassis,
Aristidis Likas:
A Greedy EM Algorithm for Gaussian Mixture Learning.
Neural Processing Letters 15(1): 77-87 (2002) |
| 2001 |
|---|
| 18 | | Aristidis Likas:
Reinforcement Learning Using the Stochastic Fuzzy Min-Max Neural Network.
Neural Processing Letters 13(3): 213-220 (2001) |
| 2000 |
|---|
| 17 | EE | Michalis K. Titsias,
Aristidis Likas:
A Probabilistic RBF Network for Classification.
IJCNN (4) 2000: 238-243 |
| 16 | EE | Costas Papaloukas,
Dimitrios I. Fotiadis,
Aristidis Likas,
Athanasios P. Liavas,
Lampros K. Michalis:
A robust knowledge-based technique for ischemia detection in noisy ECGs.
KES 2000: 768-771 |
| 1999 |
|---|
| 15 | | Nikos A. Vlassis,
Aristidis Likas:
A kurtosis-based dynamic approach to Gaussian mixture modeling.
IEEE Transactions on Systems, Man, and Cybernetics, Part A 29(4): 393-399 (1999) |
| 14 | | Aristidis Likas:
A Reinforcement Learning Approach to Online Clustering.
Neural Computation 11(8): 1915-1932 (1999) |
| 13 | | Aristidis Likas,
Isaac E. Lagaris:
Training Reinforcement Neurocontrollers Using the Polytope Algorithm.
Neural Processing Letters 9(2): 119-127 (1999) |
| 1998 |
|---|
| 12 | EE | Aristidis Likas,
Isaac E. Lagaris:
Training Reinforcement Neurocontrollers Using the Polytope Algorithm
CoRR cs.NE/9812002: (1998) |
| 11 | EE | Isaac E. Lagaris,
Aristidis Likas,
D. G. Papageorgiou:
Neural Network Methods for Boundary Value Problems Defined in Arbitrarily Shaped Domains
CoRR cs.NE/9812003: (1998) |
| 10 | EE | Isaac E. Lagaris,
Aristidis Likas,
Dimitrios I. Fotiadis:
Artificial neural networks for solving ordinary and partial differential equations.
IEEE Transactions on Neural Networks 9(5): 987-1000 (1998) |
| 1997 |
|---|
| 9 | EE | Konstantinos Blekas,
Aristidis Likas,
Andreas Stafylopatis:
A Fuzzy Neural Network Approach to Classification Based on Proximity Characteristics of Patterns.
ICTAI 1997: 323-330 |
| 8 | | Aristidis Likas,
George Papageorgiou,
Andreas Stafylopatis:
A Connectionist Approach for Solving Large Constraint Satisfaction Problems.
Appl. Intell. 7(3): 215-225 (1997) |
| 1996 |
|---|
| 7 | | Aristidis Likas,
Andreas Stafylopatis:
High Capacity Associative Memory Based on The Random Neural Network Model.
IJPRAI 10(8): 919-937 (1996) |
| 6 | | Aristidis Likas,
Konstantinos Blekas:
A Reinforcement Learning Approach Based on the Fuzzy Min-Max Neural Network.
Neural Processing Letters 4(3): 167-172 (1996) |
| 1995 |
|---|
| 5 | | Aristidis Likas,
Konstantinos Blekas,
Andreas Stafylopatis:
Parallel Recombinative Reinforcement Learning (Extended Abstract).
ECML 1995: 311-314 |
| 4 | EE | Aristidis Likas,
Andreas Stafylopatis:
A Parallel Algorithm for the Minimum Weighted Vertex Cover Problem.
Inf. Process. Lett. 53(4): 229-234 (1995) |
| 3 | | D. Kontoravdis,
Aristidis Likas,
Andreas Stafylopatis:
Discrete Optimisation Based on the Combined Use of Reinforcement and Constraint Satisfaction Schemes.
Neural Computing and Applications 3(2): 101-112 (1995) |
| 1992 |
|---|
| 2 | | D. Kontoravdis,
Aristidis Likas,
Andreas Stafylopatis:
Collision-Free Movement of an Autonomous Vehicle Using Reinforcement Learning.
ECAI 1992: 666-670 |
| 1 | EE | Andreas Stafylopatis,
Aristidis Likas:
Pictorial Information Retrieval Using the Random Neural Network.
IEEE Trans. Software Eng. 18(7): 590-600 (1992) |
