2008 |
46 | EE | Adas Gelzinis,
Antanas Verikas,
Marija Bacauskiene:
Automated speech analysis applied to laryngeal disease categorization.
Computer Methods and Programs in Biomedicine 91(1): 36-47 (2008) |
45 | EE | Antanas Verikas,
Marija Bacauskiene,
D. Valincius,
Adas Gelzinis:
Predictor output sensitivity and feature similarity-based feature selection.
Fuzzy Sets and Systems 159(4): 422-434 (2008) |
44 | EE | Jonas Guzaitis,
Antanas Verikas:
An Efficient Technique to Detect Visual Defects in Particleboards.
Informatica, Lith. Acad. Sci. 19(3): 363-376 (2008) |
2007 |
43 | EE | Adas Gelzinis,
Antanas Verikas,
Marija Bacauskiene:
Categorizing Laryngeal Images for Decision Support.
ACIVS 2007: 521-530 |
42 | EE | Marcus Ejnarsson,
Carl Magnus Nilsson,
Antanas Verikas:
Screening Paper Formation Variations on Production Line.
IEA/AIE 2007: 511-520 |
41 | EE | Cristofer Englund,
Antanas Verikas:
Combining Traditional and Neural-Based Techniques for Ink Feed Control in a Newspaper Printing Press.
Industrial Conference on Data Mining 2007: 214-227 |
40 | EE | D. Valincius,
Antanas Verikas,
Marija Bacauskiene,
Adas Gelzinis:
Evolving Committees of Support Vector Machines.
MLDM 2007: 263-275 |
39 | EE | Antanas Verikas,
Adas Gelzinis,
D. Valincius,
Marija Bacauskiene,
Virgilijus Uloza:
Multiple feature sets based categorization of laryngeal images.
Computer Methods and Programs in Biomedicine 85(3): 257-266 (2007) |
38 | EE | Antanas Verikas,
Marija Bacauskiene,
Carl Magnus Nilsson:
Estimating the amount of cyan, magenta, yellow, and black inks in arbitrary colour pictures.
Neural Computing and Applications 16(2): 187-195 (2007) |
37 | EE | Adas Gelzinis,
Antanas Verikas,
Marija Bacauskiene:
Increasing the discrimination power of the co-occurrence matrix-based features.
Pattern Recognition 40(9): 2367-2372 (2007) |
2006 |
36 | EE | Antanas Verikas,
Marija Bacauskiene,
Carl Magnus Nilsson:
Soft Computing for Assessing the Quality of Colour Prints.
IEA/AIE 2006: 701-710 |
35 | EE | Marija Bacauskiene,
Vladas Cibulskis,
Antanas Verikas:
Selecting Variables for Neural Network Committees.
ISNN (1) 2006: 837-842 |
34 | EE | Marcus Ejnarsson,
Carl Magnus Nilsson,
Antanas Verikas:
A Kernel Based Multi-resolution Time Series Analysis for Screening Deficiencies in Paper Production.
ISNN (2) 2006: 1111-1116 |
33 | EE | Antanas Verikas,
Adas Gelzinis,
Marija Bacauskiene,
Virgilijus Uloza:
Towards a computer-aided diagnosis system for vocal cord diseases.
Artificial Intelligence in Medicine 36(1): 71-84 (2006) |
32 | EE | Antanas Verikas,
Adas Gelzinis,
Marija Bacauskiene,
Virgilijus Uloza:
Integrating Global and Local Analysis of Color, Texture and Geometrical Information for Categorizing Laryngeal Images.
IJPRAI 20(8): 1187-1206 (2006) |
2005 |
31 | EE | Antanas Verikas,
Adas Gelzinis,
Marija Bacauskiene,
Virgilijus Uloza:
Intelligent Vocal Cord Image Analysis for Categorizing Laryngeal Diseases.
IEA/AIE 2005: 69-78 |
30 | EE | Cristofer Englund,
Antanas Verikas:
A SOM Based Model Combination Strategy.
ISNN (1) 2005: 461-466 |
29 | EE | Antanas Verikas,
Marija Bacauskiene:
Image analysis and fuzzy integration applied to print quality assessment.
Cybernetics and Systems 36(6): 549-564 (2005) |
28 | EE | Lars Bergman,
Antanas Verikas,
Marija Bacauskiene:
Unsupervised colour image segmentation applied to printing quality assessment.
Image Vision Comput. 23(4): 417-425 (2005) |
2004 |
27 | EE | Antanas Verikas,
Marija Bacauskiene,
Adas Gelzinis:
Leverages Based Neural Networks Fusion.
ICONIP 2004: 446-451 |
26 | | Lars Bergman,
Antanas Verikas:
Intelligent monitoring of the offset printing process.
Neural Networks and Computational Intelligence 2004: 173-178 |
25 | EE | Marija Bacauskiene,
Antanas Verikas:
The Evidence Theory Based Post-Processing of Colour Images.
Informatica, Lith. Acad. Sci. 15(3): 315-328 (2004) |
24 | EE | Marija Bacauskiene,
Antanas Verikas:
Selecting salient features for classification based on neural network committees.
Pattern Recognition Letters 25(16): 1879-1891 (2004) |
2003 |
23 | EE | Antanas Verikas,
Marija Bacauskiene,
Kerstin Malmqvist:
Selecting Salient Features for Classification Committees.
ICANN 2003: 35-42 |
22 | | Antanas Verikas,
Lars Bergman,
Kerstin Malmqvist,
Marija Bacauskiene:
Neural Modelling and Control of the Offset Printing Process.
Neural Networks and Computational Intelligence 2003: 130-135 |
21 | EE | Antanas Verikas,
Marija Bacauskiene,
Alvydas Dosinas,
Vacys Bartkevicius,
Adas Gelzinis,
Mindaugas Vaitkunas,
Arunas Lipnickas:
An intelligent system for tuning magnetic field of a cathode ray tube deflection yoke.
Knowl.-Based Syst. 16(3): 161-164 (2003) |
20 | EE | Antanas Verikas,
Marija Bacauskiene,
Kerstin Malmqvist:
Learning an Adaptive Dissimilarity Measure for Nearest Neighbour Classification.
Neural Computing and Applications 11(3-4): 203-209 (2003) |
2002 |
19 | EE | Antanas Verikas,
Arunas Lipnickas,
Kerstin Malmqvist:
Selecting Neural Networks for Making a Committee Decision.
ICANN 2002: 420-425 |
18 | EE | Antanas Verikas,
Arunas Lipnickas,
Kerstin Malmqvist:
Selecting Neural Networks for a Committee Decision.
Int. J. Neural Syst. 12(5): 351-361 (2002) |
17 | | Antanas Verikas,
Arunas Lipnickas:
Fusing Neural Networks Through Space Partitioning and Fuzzy Integration.
Neural Processing Letters 16(1): 53-65 (2002) |
16 | EE | Antanas Verikas,
Marija Bacauskiene:
Feature selection with neural networks.
Pattern Recognition Letters 23(11): 1323-1335 (2002) |
2001 |
15 | EE | Antanas Verikas,
Adas Gelzinis,
Kerstin Malmqvist,
Marija Bacauskiene:
Using Unlabelled Data to Train a Multilayer Perceptron.
ICAPR 2001: 40-49 |
14 | EE | Antanas Verikas,
Kerstin Malmqvist,
Marija Bacauskiene:
Combining neural networks, fuzzy sets, and the evidence theory based techniques for detecting colour specks.
Journal of Intelligent and Fuzzy Systems 10(2): 117-130 (2001) |
13 | | Antanas Verikas,
Adas Gelzinis,
Kerstin Malmqvist:
Using Unlabelled Data to Train a Multilayer Perceptron.
Neural Processing Letters 14(3): 179-201 (2001) |
2000 |
12 | EE | Antanas Verikas,
Kerstin Malmqvist,
Marija Bacauskiene:
Combining Neural Networks, Fuzzy Sets, and Evidence Theory Based Approaches for Analyzing Color Images.
IJCNN (2) 2000: 297 |
11 | EE | Antanas Verikas,
Kerstin Malmqvist,
Marija Bacauskiene,
Lars Bergman:
Monitoring the De-Inking Process through Neural Network-Based Colour Image Analysis.
Neural Computing and Applications 9(2): 142-151 (2000) |
10 | EE | Antanas Verikas,
Kerstin Malmqvist,
Lars Bergman:
Neural Networks Based Colour Measuring for Process Monitoring and Control in Multicoloured Newspaper Printing.
Neural Computing and Applications 9(3): 227-242 (2000) |
9 | EE | Antanas Verikas,
Adas Gelzinis:
Training neural networks by stochastic optimisation.
Neurocomputing 30(1-4): 153-172 (2000) |
1999 |
8 | | Antanas Verikas,
Adas Gelzinis,
Kerstin Malmqvist:
Using Labelled and Unlabelled Data to Train a Multilayer Perceptron for Colour Classification in Graphic Arts.
IEA/AIE 1999: 550-559 |
7 | | Antanas Verikas,
Kerstin Malmqvist,
Marija Bacauskiene,
Lars Bergman:
Possibilistic Neural Network Training for Detecting Color Specks.
SIP 1999: 323-327 |
6 | EE | Adas Gelzinis,
Antanas Verikas,
Kerstin Malmqvist:
Quality Function for Unsupervised Classification and its Use in Graphic Arts.
JACIII 3(6): 532-540 (1999) |
5 | EE | Antanas Verikas,
Arunas Lipnickas,
Kerstin Malmqvist,
Marija Bacauskiene,
Adas Gelzinis:
Soft combination of neural classifiers: A comparative study.
Pattern Recognition Letters 20(4): 429-444 (1999) |
1998 |
4 | | Antanas Verikas,
Kerstin Malmqvist,
Marija Bacauskiene,
Arunas Lipnickas:
Soft Fusion of Neural Classifiers.
ICONIP 1998: 195-198 |
3 | | Antanas Verikas,
Kerstin Malmqvist,
Lars Bergman,
Mikael Signahl:
Colour Classification by Neural Networks in Graphic Arts.
Neural Computing and Applications 7(1): 52-64 (1998) |
1997 |
2 | EE | Antanas Verikas,
Kerstin Malmqvist,
Lars Bergman:
Colour image segmentation by modular neural network.
Pattern Recognition Letters 18(2): 173-185 (1997) |
1992 |
1 | EE | Antanas Verikas,
Marija Bacauskiene,
S. J. Vilunas,
D. R. Skaisgiris:
Adaptive character recognition system.
Pattern Recognition Letters 13(3): 207-212 (1992) |