J. Kurek

发表

Multistage classification by using logistic regression and neural networks for assessment of financial condition of company

Stanislaw Osowski, Bartosz Swiderski, Jaroslaw Kurek, 2012, Decis. Support Syst..

Improved computer recognition of Fuhrman grading system in analysis of Clear-Cell Renal Carcinoma

S. Osowski, J. Kurek, M. Kruk, 2015 .

Scientific Research Activity and GDP. An Analysis of Causality Based on 144 Countries From Around the World

B. Świderski, J. Kurek, W. Dębski, 2018 .

Data augmentation techniques for transfer learning improvement in drill wear classification using convolutional neural network

A. Orłowski, J. Górski, B. Świderski, 2019, Machine Graphics and Vision.

Random CNN structure: tool to increase generalization ability in deep learning

S. Osowski, I. Lugowska, B. Świderski, 2021, EURASIP J. Image Video Process..

Initial study on the use of support vector machine (SVM) in tool condition monitoring in chipboard drilling

J. Górski, J. Kurek, M. Kruk, 2019, European Journal of Wood and Wood Products.

Prediction of Blueberry (Vaccinium corymbosum L.) Yield Based on Artificial Intelligence Methods

G. Niedbała, T. Wojciechowski, B. Świderski, 2022, Agriculture.

Ensemble of classifiers and wavelet transformation for improved recognition of Fuhrman grading in clear-cell renal carcinoma

Stanislaw Osowski, Tomasz Markiewicz, R. Koktysz, 2017 .

Diagnostic feature selection for efficient recognition of different faults of rotor bars in the induction machine

S. Osowski, J. Kurek, S. Osowski, 2010 .

Advanced Feature Extraction Methods from Images of Drillings in Melamine Faced Chipboard for Automatic Diagnosis of Drill Wear

J. Kurek, A. Krupa, M. Kruk, 2023, Sensors.

Improved Drill State Recognition during Milling Process Using Artificial Intelligence

K. Szymanowski, J. Kurek, A. Krupa, 2023, Sensors.

A UTOMATED SOIL PROFILE GENERATION METHODS ON THE BASIS OF DMT AND CPT DATA

P. Bilski, J. Kurek, M. Kruk, 2014 .

Time-efficient approach to drill condition monitoring based on images of holes drilled in melamine faced chipboard

Izabella Antoniuk, P. Czarniak, Jaroslaw Kurek, 2020 .

Deep learning methods for drill wear classification based on images of holes drilled in melamine faced chipboard

P. Czarniak, J. Kurek, Albina Jegorowa, 2020, Wood Science and Technology.

Effect of Nitrogen Ion Implantation on the Tool Life Used in Particleboard CNC Drilling

Z. Werner, M. Barlak, J. Wilkowski, 2022, Materials.

Automatic Estimation of Drill Wear Based on Images of Holes Drilled in Melamine Faced Chipboard with Machine Learning Algorithms

B. Świderski, J. Kurek, A. Krupa, 2023, Forests.

Evaluation of selected elements of the potential of the Polish Armed Forces

J. Kurek, 2021, Systemy Logistyczne Wojsk.

Melanoma recognition using extended set of descriptors and classifiers

Stanislaw Osowski, Michal Kruk, Bartosz Swiderski, 2015, EURASIP Journal on Image and Video Processing.

Melanoma recognition using extended set of descriptors and classifiers

S. Osowski, B. Świderski, J. Kurek, 2015, EURASIP J. Image Video Process..

False-positive reduction in computer-aided mass detection using mammographic texture analysis and classification

Ezzeddine Zagrouba, Walid Barhoumi, Sami Dhahbi, 2018, Comput. Methods Programs Biomed..

Novel methods of image description and ensemble of classifiers in application to mammogram analysis

Stanislaw Osowski, Walid Barhoumi, Michal Kruk, 2017, Expert Syst. Appl..

Deep learning and non-negative matrix factorization in recognition of mammograms

Walid Barhoumi, Michal Kruk, Bartosz Swiderski, 2017, International Conference on Graphic and Image Processing.

Deep learning versus classical neural approach to mammogram recognition

Walid Barhoumi, Stanislaw Osowski, Michal Kruk, 2018 .

Application of Machine Learning Algorithms for Tool Condition Monitoring in Milling Chipboard Process

K. Szymanowski, J. Kurek, M. Kruk, 2023, Sensors.

Support vector machine for fault diagnosis of the broken rotor bars of squirrel-cage induction motor

Stanislaw Osowski, Jaroslaw Kurek, S. Osowski, 2010, Neural Computing and Applications.

Diagnostic System of Drill Condition in Laminated Chipboard Drilling Process

Michal Kruk, Bartosz Swiderski, Jaroslaw Kurek, 2017 .

Milk duct segmentation in microscopic HE images of breast cancer tissues

S. Osowski, A. Orłowski, L. Chmielewski, 2017 .

Texture characterization based on the Kolmogorov-Smirnov distance

Stanislaw Osowski, Michal Kruk, Bartosz Swiderski, 2015, Expert Syst. Appl..

Soils Classification System on the Basis of Dmt and Cpt Data

Piotr Bilski, Michal Kruk, Simon Rabarijoely, 2015 .

Vehicle Detection and Recognition Approach in Multi-Scale Traffic Monitoring System via Graph-Based Data Optimization

Sheikh Badar ud din Tahir, J. Kurek, Grzegorz Wieczorek, 2023, Sensors.

Random CNN structure: tool to increase generalization ability in deep learning

S. Osowski, I. Lugowska, B. Świderski, 2022, EURASIP Journal on Image and Video Processing.

Feature Selection for 'Orange Skin' Type Surface Defect in Furniture Elements

Michal Kruk, Arkadiusz Orlowski, Leszek J. Chmielewski, 2018, ICAISC.

Textural features based on run length encoding in the classification of furniture surfaces with the orange skin defect

A. Orłowski, L. Chmielewski, J. Górski, 2019, Machine Graphics and Vision.