Robert Burduk

Knowl. Based Syst., 2024

Improved Pest Detection in Insect Larvae Rearing with Pseudo-Labelling and Spatio-Temporal Masking.

[BibT_eX]

[DOI]

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

End-to-end Solution for Tenebrio Molitor Rearing Monitoring with Uncertainty Estimation and Domain Shift Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Optimisation of Battery Energy Storage Systems Capacity for Purpose to Reduce Energy Cost.

[BibT_eX]

[DOI]

Pawel Parczyk

Proceedings of the Computer Information Systems and Industrial Management, 2024

2023

Prediction of the remaining time of the foraging activity of honey bees using spatio-temporal correction and periodic model re-fitting.

[BibT_eX]

[DOI]

Comput. Electron. Agric., February, 2023

Mixing Augmentation and Knowledge-Based Techniques in Unsupervised Domain Adaptation for Segmentation of Edible Insect States.

[BibT_eX]

[DOI]

Proceedings of the 18th International Joint Conference on Computer Vision, 2023

Recall and Selectivity Normalized in Class Labels as a Classification Performance Metric.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2023

Combining Linear Classifiers Using Score Function Based on Distance to Decision Boundary.

[BibT_eX]

[DOI]

Andrzej Kasprzak

Proceedings of the Artificial Intelligence and Soft Computing, 2023

Battery Management System for Polish Hybrid Residential Photovoltaic Power Plants.

[BibT_eX]

[DOI]

Pawel Parczyk

Proceedings of the Progress on Pattern Classification, Image Processing and Communications, 2023

2022

Multi-Parameter Predictive Model of Mobile Robot's Battery Discharge for Intelligent Mission Planning in Multi-Robot Systems.

[BibT_eX]

[DOI]

Sensors, 2022

Probability-driven scoring functions in combining linear classifiers.

[BibT_eX]

[DOI]

J. Univers. Comput. Sci., 2022

Advances and Practical Applications of Deep and Shallow Machine Learning.

[BibT_eX]

[DOI]

J. Univers. Comput. Sci., 2022

Subspace-based decision trees integration.

[BibT_eX]

[DOI]

Inf. Sci., 2022

Advances in Computer Recognition, Image Processing and Communications.

[BibT_eX]

[DOI]

Entropy, 2022

Relearning Ensemble Selection Based on New Generated Features.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Information and Database Systems - 14th Asian Conference, 2022

2021

Linear classifier combination via multiple potential functions.

[BibT_eX]

[DOI]

Pattern Recognit., 2021

Fusion of linear base classifiers in geometric space.

[BibT_eX]

[DOI]

Pawel Ksieniewicz

Pawel Zyblewski

Knowl. Based Syst., 2021

Clustering and Weighted Scoring Algorithm Based on Estimating the Number of Clusters.

[BibT_eX]

[DOI]

Jakub Klikowski

Proceedings of the Computational Science - ICCS 2021, 2021

Distance Metrics in Clustering and Weighted Scoring Algorithm.

[BibT_eX]

[DOI]

Jakub Klikowski

Proceedings of the Progress in Image Processing, Pattern Recognition and Communication Systems, 2021

2020

Integration of Decision Trees Using Distance to Centroid and to Decision Boundary.

[BibT_eX]

[DOI]

J. Univers. Comput. Sci., 2020

Decision Tree Integration Using Dynamic Regions of Competence.

[BibT_eX]

[DOI]

Entropy, 2020

Classification Performance Metric for Imbalance Data Based on Recall and Selectivity Normalized in Class Labels.

[BibT_eX]

[DOI]

CoRR, 2020

Combining Linear Classifiers Using Probability-Based Potential Functions.

[BibT_eX]

[DOI]

IEEE Access, 2020

Weighted Scoring in Geometric Space for Decision Tree Ensemble.

[BibT_eX]

[DOI]

IEEE Access, 2020

Clustering and Weighted Scoring in Geometric Space Support Vector Machine Ensemble for Highly Imbalanced Data Classification.

[BibT_eX]

[DOI]

Pawel Ksieniewicz

Proceedings of the Computational Science - ICCS 2020, 2020

Dynamic Ensemble Selection - Application to Classification of Cutting Tools.

[BibT_eX]

[DOI]

Paulina Heda

Izabela Rojek

Proceedings of the Computer Information Systems and Industrial Management, 2020

Novel Approach to Gentle AdaBoost Algorithm with Linear Weak Classifiers.

[BibT_eX]

[DOI]

Wojciech Bozejko

Szymon Zacher

Proceedings of the Intelligent Information and Database Systems - 12th Asian Conference, 2020

2019

Integration and Selection of Linear SVM Classifiers in Geometric Space.

[BibT_eX]

[DOI]

J. Univers. Comput. Sci., 2019

Modified Score Function and Linear Weak Classifiers in LogitBoost Algorithm.

[BibT_eX]

[DOI]

Wojciech Bozejko

Proceedings of the Image Processing and Communications, 2019

Combination of Linear Classifiers Using Score Function - Analysis of Possible Combination Strategies.

[BibT_eX]

[DOI]

Proceedings of the Progress in Computer Recognition Systems, 2019

Gentle AdaBoost Algorithm with Score Function Dependent on the Distance to Decision Boundary.

[BibT_eX]

[DOI]

Wojciech Bozejko

Proceedings of the Computer Information Systems and Industrial Management, 2019

2018

Integration of Linear SVM Classifiers in Geometric Space Using the Median.

[BibT_eX]

[DOI]

Proceedings of the Image Processing and Communications Challenges 10, 2018

Integration Base Classifiers in Geometry Space by Harmonic Mean.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence and Soft Computing, 2018

The Use of Geometric Mean in the Process of Integration of Three Base Classifiers.

[BibT_eX]

[DOI]

Andrzej Kasprzak

Proceedings of the Computer Information Systems and Industrial Management, 2018

2017

The AdaBoost Algorithm with Linear Modification of the Weights.

[BibT_eX]

[DOI]

Proceedings of the Image Processing and Communications Challenges 9, 2017

Integration Base Classifiers Based on Their Decision Boundary.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence and Soft Computing, 2017

Drift Detection Algorithm Using the Discriminant Function of the Base Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017, 2017

Classifier Selection for Motor Imagery Brain Computer Interface.

[BibT_eX]

[DOI]

Izabela Rejer

Proceedings of the Computer Information Systems and Industrial Management, 2017

2016

Active Learning Algorithm Using the Discrimination Function of the Base Classifiers.

[BibT_eX]

[DOI]

Proceedings of the Image Processing and Communications Challenges 8, 2016

Dynamic Ensemble Selection Using Discriminant Functions and Normalization Between Class Labels - Approach to Binary Classification.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence and Soft Computing, 2016

Ensemble of Classifiers with Modification of Confidence Values.

[BibT_eX]

[DOI]

Proceedings of the Computer Information Systems and Industrial Management, 2016

Homogeneous Ensemble Selection - Experimental Studies.

[BibT_eX]

[DOI]

Paulina Heda

Proceedings of the Hard and Soft Computing for Artificial Intelligence, 2016

2015

Classifier Selection Uses Decision Profiles in Binary Classification Task.

[BibT_eX]

[DOI]

Proceedings of the Image Processing and Communications Challenges 7, 2015

Ensemble Selection Based on Discriminant Functions in Binary Classification Task.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2015, 2015

Discriminant Function Selection in Binary Classification Task.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015, 2015

Static Classifier Selection with Interval Weights of Base Classifiers.

[BibT_eX]

[DOI]

Krzysztof Walkowiak

Proceedings of the Intelligent Information and Database Systems - 7th Asian Conference, 2015

2014

Method of Static Classifiers Selection Using the Weights of Base Classifiers.

[BibT_eX]

[DOI]

Proceedings of the Soft Computing in Computer and Information Science, 2014

The AdaBoost Algorithm with the Imprecision Determine the Weights of the Observations.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Information and Database Systems - 6th Asian Conference, 2014

2013

Classifier fusion with interval-valued weights.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2013

Construction of Sequential Classifier Based on MacArthur's Overlapping Niches Model.

[BibT_eX]

[DOI]

Proceedings of the Image Processing and Communications Challenges 5, 2013

Construction of Sequential Classifier Based on Broken Stick Model.

[BibT_eX]

[DOI]

Proceedings of the Hybrid Artificial Intelligent Systems - 8th International Conference, 2013

The Method of Improving the Structure of the Decision Tree Given by the Experts.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013, 2013

Construction of Sequential Classifier Using Confusion Matrix.

[BibT_eX]

[DOI]

Proceedings of the Computer Information Systems and Industrial Management, 2013

2012

Imprecise information in Bayes classifier.

[BibT_eX]

[DOI]

Pattern Anal. Appl., 2012

On the Bounds on Optimal Bayes Error in the Task of Multiple Data Sources.

[BibT_eX]

[DOI]

Proceedings of the Image Processing and Communications Challenges 4, 2012

New AdaBoost Algorithm Based on Interval-Valued Fuzzy Sets.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2012, 2012

Recognition Task with Feature Selection and Weighted Majority Voting Based on Interval-Valued Fuzzy Sets.

[BibT_eX]

[DOI]

Proceedings of the Computational Collective Intelligence. Technologies and Applications, 2012

Decomposition of Classification Task with Selection of Classifiers on the Medical Diagnosis Example.

[BibT_eX]

[DOI]

Marcin Zmyslony

Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012

Comparison of Cost for Zero-One and Stage-Dependent Fuzzy Loss Function.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Information and Database Systems - 4th Asian Conference, 2012

2011

Some Properties of Binary Classifier with Fuzzy-Valued Loss Function.

[BibT_eX]

[DOI]

Proceedings of the Computer Recognition Systems 4, 2011

Costs-Sensitive Classification in Two-Stage Binary Classifier.

[BibT_eX]

[DOI]

Andrzej Kasprzak

Proceedings of the Image Processing and Communications Challenges 3, 2011

Estimations of the Error in Bayes Classifier with Fuzzy Observations.

[BibT_eX]

[DOI]

Proceedings of the Computational Collective Intelligence. Technologies and Applications, 2011

Costs-Sensitive Classification in Multistage Classifier with Fuzzy Observations of Object Features.

[BibT_eX]

[DOI]

Proceedings of the Hybrid Artificial Intelligent Systems - 6th International Conference, 2011

2010

Classification error in Bayes multistage recognition task with fuzzy observations.

[BibT_eX]

[DOI]

Pattern Anal. Appl., 2010

Some characteristics of an error in the two-class problem with fuzzy observations.

[BibT_eX]

[DOI]

Proceedings of the 10th International Conference on Intelligent Systems Design and Applications, 2010

A Partition of Feature Space Based on Information Energy in Classification with Fuzzy Observations.

[BibT_eX]

[DOI]

Proceedings of the Image Processing and Communications Challenges 2, 2010

Randomness and Fuzziness in Bayes Multistage Classifier.

[BibT_eX]

[DOI]

Proceedings of the Hybrid Artificial Intelligence Systems, 5th International Conference, 2010

2009

Intuitionistic Fuzzy Observations in Local Optimal Hierarchical Classifier.

[BibT_eX]

[DOI]

Proceedings of the Computer Recognition Systems 3, 2009

Interval-Valued Fuzzy Observations in Bayes Classifier.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data Engineering and Automated Learning, 2009

Bayes Multistage Classifier and Boosted C4.5 Algorithm in Acute Abdominal Pain Diagnosis.

[BibT_eX]

[DOI]

Michal Wozniak

Proceedings of the Man-Machine Interactions, 2009

Probability Error in Bayes Optimal Classifier with Intuitionistic Fuzzy Observations.

[BibT_eX]

[DOI]

Proceedings of the Image Analysis and Recognition, 6th International Conference, 2009

Probability Error in Global Optimal Hierarchical Classifier with Intuitionistic Fuzzy Observations.

[BibT_eX]

[DOI]

Proceedings of the Hybrid Artificial Intelligence Systems, 4th International Conference, 2009

2008

Stage-Dependent Fuzzy-valued Loss Function in Two-Stage Binary Classifier.

[BibT_eX]

[DOI]

Proceedings of the Innovations in Hybrid Intelligent Systems, 2008

Possibility of Use a Fuzzy Loss Function in Medical Diagnostics.

[BibT_eX]

[DOI]

Proceedings of the Information Technologies in Biomedicine, 2008

Classification Accuracy in Local Optimal Strategy of Multistage Recognition with Fuzzy Data.

[BibT_eX]

[DOI]

Proceedings of the Computer Recognition Systems 2, 2008

2007

Fuzzy Data in Local Optimal Strategy of Multistage Recognition.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Computer Information Systems and Industrial Management Applications, 2007

2006

Two-stage binary classifier with fuzzy-valued loss function.

[BibT_eX]

[DOI]

Marek Kurzynski

Pattern Anal. Appl., 2006

2005

Probability of Misclassification in Bayesian Hierarchical Classifier.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Information Processing and Web Mining, 2005

Selection of Fuzzy-Valued Loss Function in Two Stage Binary Classifier.

[BibT_eX]

[DOI]