Profile Details

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Hire Dr. Jarosław K.

Poland

USD 60 /hr

Machine learning, deep learning, credit risk, credit scoring, https://www.deeptechnology.ai

Profile Summary

Machine learning, deep learning, credit risk, credit scoring, more information at https://www.deeptechnology.ai

Subject Matter Expertise

• ★ Machine Learning
• ★ Deep Learning
• ☆ Data Analysis
• ☆ Image Processing
• ☆ Python

Services

• Writing
• Data & AI

Writing Technical Writing

Data & AI Statistical Analysis, Algorithm Design-Non ML, Data Visualization

Work Experience

assistant professor

Warsaw University of Life Sciences

September 2008 - Present

Education

PhD (Faculty of Electrical Engineering)

Warsaw University of Technology

September 2004 - June 2008

master of science /engineer (Faculty of Electrical Engineering)

Warsaw University of Technology

September 1999 - June 2004

Certifications

• Certification details not provided.

Publications

JOURNAL ARTICLE

Kurek, J., Swiderski, B., Osowski, S., Kruk, M., Barhoumi, W.(2018). Deep learning versus classical neural approach to mammogram recognition . Bulletin of the Polish Academy of Sciences: Technical Sciences. p. 831-840.

Dhahbi, S., Barhoumi, W., Kurek, J., Swiderski, B., Kruk, M., Zagrouba, E.(2018). False-positive reduction in computer-aided mass detection using mammographic texture analysis and classification . Computer Methods and Programs in Biomedicine. 160. p. 75-83.

Dębski, W., Świderski, B., Kurek, J.(2018). Scientific research activity and GDP. An analysis of causality based on 144 countries from around the world . Contemporary Economics. 12. (3). p. 301-314.

Swiderski, B., Osowski, S., Kurek, J., Kruk, M., Lugowska, I., Rutkowski, P., Barhoumi, W.(2017). Novel methods of image description and ensemble of classifiers in application to mammogram analysis . Expert Systems with Applications. 81. p. 67-78.

Kruk, M., Kurek, J., Osowski, S., Koktysz, R., Swiderski, B., Markiewicz, T.(2017). Ensemble of classifiers and wavelet transformation for improved recognition of Fuhrman grading in clear-cell renal carcinoma . Biocybernetics and Biomedical Engineering. 37. (3). p. 357-364.

Kruk, M., Świderski, B., Osowski, S., Kurek, J., Słowińska, M., Walecka, I.(2015). Melanoma recognition using extended set of descriptors and classifiers . Eurasip Journal on Image and Video Processing. 2015. (1). p. 1-10.

Swiderski, B., Osowski, S., Kruk, M., Kurek, J.(2015). Texture characterization based on the Kolmogorov-Smirnov distance . Expert Systems with Applications. 42. (1). p. 503-509.

Swiderski, B., Kurek, J., Osowski, S.(2012). Multistage classification by using logistic regression and neural networks for assessment of financial condition of company . Decision Support Systems. 52. (2). p. 539-547.

Kurek, J., Świderski, B., Osowski, S.(2011). Assessment of financial condition of companies using neural networks,Szacowanie kondycji finansowej prze{ogonek}dsiebiorstw przy pomocy sieci neuronowych . Przeglad Elektrotechniczny. 87. (5). p. 88-91.

Kurek, J., Osowski, S.(2010). Diagnostic feature selection for efficient recognition of different faults of rotor bars in the induction machine . Przeglad Elektrotechniczny. 86. (1). p. 121-123.

Kurek, J., Osowski, S.(2010). Support vector machine for fault diagnosis of the broken rotor bars of squirrel-cage induction motor . Neural Computing and Applications. 19. (4). p. 557-564.

BOOK

Świderski, B., Kruk, M., Wieczorek, G., Kurek, J., Śmietańska, K., Chmielewski, L.J., Górski, J., Orłowski, A.(2018). Feature selection for ‘Orange skin’ type surface defect in furniture elements . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10842 LNAI. p. 81-91.

Kruk, M., Świderski, B., Śmietańska, K., Kurek, J., Chmielewski, L.J., Górski, J., Orłowski, A.(2017). Detection of ‘orange skin’ type surface defects in furniture elements with the use of textural features . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10244 LNCS. p. 402-411.

Osowski, S., Kruk, M., Koktysz, R., Kurek, J.(2013). Image processing for localization and parameterization of the glandular ducts of colon in inflammatory bowel diseases . Image Processing: Concepts, Methodologies, Tools, and Applications. 2-3. p. 688-708.

Osowski, S., Kruk, M., Koktysz, R., Kurek, J.(2011). Image processing for localization and parameterization of the glandular ducts of colon in inflammatory bowel diseases . Computational Modeling and Simulation of Intellect: Current State and Future Perspectives. p. 1-24.

CONFERENCE PAPER

Kurek, J., Wieczorek, G., Swiderski, B., Kruk, M., Jegorowa, A., Gorski, J.(2018). Automatic identification of drill condition during drilling process in standard laminated chipboard with the use of long short-term memory (LSTM) . Proceedings of 2018 19th International Conference Computational Problems of Electrical Engineering, CPEE 2018.

Jacek Kubica, B., Kurek, J.(2018). Interval arithmetic, hull-consistency enforcing and algorithmic differentiation using a template-based package . Proceedings of 2018 19th International Conference Computational Problems of Electrical Engineering, CPEE 2018.

Kurek, J., Swiderski, B., Jegorowa, A., Kruk, M., Osowski, S.(2017). Deep learning in assessment of drill condition on the basis of images of drilled holes . Proceedings of SPIE - The International Society for Optical Engineering. 10225.

ŚWiderski, B., Kruk, M., Osowski, S., Wieczorek, G., Kurek, J., Chmielewski, L.J., Orłowski, A.(2017). Milk duct segmentation in microscopic HE images of breast cancer tissues . MATEC Web of Conferences. 125.

Swiderski, B., Kurek, J., Osowski, S., Kruk, M., Jegorowa, A.(2017). Diagnostic System of Drill Condition in Laminated Chipboard Drilling Process . MATEC Web of Conferences. 125.

Kurek, J., Wieczorek, G., Kruk, B.S.M., Jegorowa, A., Osowski, S.(2017). Transfer learning in recognition of drill wear using convolutional neural network . Proceedings of 2017 18th International Conference on Computational Problems of Electrical Engineering, CPEE 2017.

Swiderski, B., Kurek, J., Osowski, S., Kruk, M., Barhoumi, W.(2017). Deep learning and non-negative matrix factorization in recognition of mammograms . Proceedings of SPIE - The International Society for Optical Engineering. 10225.

Kurek, J., Świderski, B., Dhahbi, S., Kruk, M., Barhoumi, W., Wieczorek, G., Zagrouba, E.(2016). Chaos theory-based quantification of ROIs for mammogram classification . Computational Vision and Medical Image Processing V - Proceedings of 5th Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VipIMAGE 2015. p. 187-191.

Kruk, M., Kurek, J., Osowski, S., Koktysz, R.(2016). Improved computer recognition of Fuhrman grading system in analysis of Clear-Cell Renal Carcinoma . Computational Vision and Medical Image Processing V - Proceedings of 5th Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VipIMAGE 2015. p. 221-226.

Kruk, M., Jegorowa, A., Kurek, J., Osowski, S., Gorski, J.(2016). Automatic recognition of drill condition on the basis of images of drilled holes . Proceedings of 2016 17th International Conference Computational Problems of Electrical Engineering, CPEE 2016.

Kurek, J., Osowski, S.(2008). Support vector machine for diagnosis of the bars of cage inductance motor . Proceedings of the 15th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2008. p. 1022-1025.