RTU Research Outputs and Resources: Reasearch Staff

Information about Author

Name, Surname:

Vilens Jumutcs

Department:

(33700) Lietišķo datorsistēmu institūts

Field of research:

1. Natural sciences

Sub-field of research:

1.2 Computer and information sciences

Research interests:

SVM, machine learning

E-mail:

Vilens.Jumutcs(at)rtu.lv

Publications

11 items found, displaying 1 to 10.

Hybrid Approach to Colony-Forming Unit Counting Problem Using Multi-Loss U-Net Reformulation
(2023)

Vilens Jumutcs, Artjoms Supoņenkovs, Andrejs Bondarenko, Dmitrijs Bļizņuks, Alexey Lihachev
Scientific article indexed in SCOPUS or WOS database

Multi-Loss U-Net Reformulation as an Efficient Solution to the Colony-Forming Unit Counting Problem
(2023)

Vilens Jumutcs, Dmitrijs Bļizņuks, Alexey Lihachev
Full-text conference paper published in conference proceedings indexed in SCOPUS or WOS database

Classification Tree Extraction from Trained Artificial Neural Networks
(2016)

Andrejs Bondarenko, Ludmila Aleksejeva, Vilens Jumutcs, Arkādijs Borisovs
Scientific article indexed in SCOPUS or WOS database

Extraction of Interpretable Rules from Piecewise-Linear Approximation of a Nonlinear Classifier Using Clustering-Based Decomposition
(2011)

Andrejs Bondarenko, Vilens Jumutcs
Full-text conference paper published in other conference proceedings

Polytope Classifier: A Symbolic Knowledge Extraction from Piecewise-Linear Support Vector Machine
(2011)

Vilens Jumutcs, Andrejs Bondarenko
Full-text conference paper published in other conference proceedings

Inferring Optimal Kernel Hyperparameters Using Cox Regression for Cancer Outcome Prediction
(2010)

Vilens Jumutcs, Pawel Zayakin
Full-text conference paper published in other conference proceedings

Topological Expansion for Smoothing the Kernel Based on Biomedical and Microarray Data
(2010)

Vilens Jumutcs, Pawel Zayakin
Full-text conference paper published in other conference proceedings

On the Power of Topological kernel in Microarray-Based Detection of Cancer
(2010)

Vilens Jumutcs, Pawel Zayakin
Full-text conference paper published in other conference proceedings

Antigen Reduction Applied to Support Vector Machine Classification for Melanoma-Related Diagnostics
(2009)

Vilens Jumutcs, Pawel Zayakin, Aija Linē
Scientific article indexed in ERIH database, in INT1 or INT2 category journals

Applying ANN Ensembles to Melanoma-Related Diagnostics on Cancer Patients
(2008)

Vilens Jumutcs, Aija Linē, Pāvels Zajakins
Publications in RTU scientific journal

Projects

2 items found, displaying 1 to 2.

Avenantramīdu koncentrātu inovatīvu ieguves tehnoloģiju ieviešana bioloģiski aktīvu produktu ražošanā
RTU pētniecības

Māra Jure

Informācijas saplūšana izkliedētās intelektuālajās sistēmās
Informācijas tehnoloģijas

Aleksandrs Vališevskis

Information about Author

Publications

Hybrid Approach to Colony-Forming Unit Counting Problem Using Multi-Loss U-Net Reformulation (2023)

Multi-Loss U-Net Reformulation as an Efficient Solution to the Colony-Forming Unit Counting Problem (2023)

Classification Tree Extraction from Trained Artificial Neural Networks (2016)

Extraction of Interpretable Rules from Piecewise-Linear Approximation of a Nonlinear Classifier Using Clustering-Based Decomposition (2011)

Polytope Classifier: A Symbolic Knowledge Extraction from Piecewise-Linear Support Vector Machine (2011)

Inferring Optimal Kernel Hyperparameters Using Cox Regression for Cancer Outcome Prediction (2010)

Topological Expansion for Smoothing the Kernel Based on Biomedical and Microarray Data (2010)

On the Power of Topological kernel in Microarray-Based Detection of Cancer (2010)

Antigen Reduction Applied to Support Vector Machine Classification for Melanoma-Related Diagnostics (2009)

Applying ANN Ensembles to Melanoma-Related Diagnostics on Cancer Patients (2008)

Projects

Avenantramīdu koncentrātu inovatīvu ieguves tehnoloģiju ieviešana bioloģiski aktīvu produktu ražošanā RTU pētniecības

Informācijas saplūšana izkliedētās intelektuālajās sistēmās Informācijas tehnoloģijas

Hybrid Approach to Colony-Forming Unit Counting Problem Using Multi-Loss U-Net Reformulation
(2023)

Multi-Loss U-Net Reformulation as an Efficient Solution to the Colony-Forming Unit Counting Problem
(2023)

Classification Tree Extraction from Trained Artificial Neural Networks
(2016)

Extraction of Interpretable Rules from Piecewise-Linear Approximation of a Nonlinear Classifier Using Clustering-Based Decomposition
(2011)

Polytope Classifier: A Symbolic Knowledge Extraction from Piecewise-Linear Support Vector Machine
(2011)

Inferring Optimal Kernel Hyperparameters Using Cox Regression for Cancer Outcome Prediction
(2010)

Topological Expansion for Smoothing the Kernel Based on Biomedical and Microarray Data
(2010)

On the Power of Topological kernel in Microarray-Based Detection of Cancer
(2010)

Antigen Reduction Applied to Support Vector Machine Classification for Melanoma-Related Diagnostics
(2009)

Applying ANN Ensembles to Melanoma-Related Diagnostics on Cancer Patients
(2008)

Avenantramīdu koncentrātu inovatīvu ieguves tehnoloģiju ieviešana bioloģiski aktīvu produktu ražošanā
RTU pētniecības

Informācijas saplūšana izkliedētās intelektuālajās sistēmās
Informācijas tehnoloģijas