Obserwuj
Jarosław Kurek
Jarosław Kurek
Institute of Information Technology, Warsaw University of Life Sciences
Zweryfikowany adres z sggw.edu.pl - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Support vector machine for fault diagnosis of the broken rotor bars of squirrel-cage induction motor
J Kurek, S Osowski
Neural Computing and Applications 19, 557-564, 2010
762010
Melanoma recognition using extended set of descriptors and classifiers
M Kruk, B Świderski, S Osowski, J Kurek, M Słowińska, I Walecka
EURASIP journal on Image and Video Processing 2015, 1-10, 2015
492015
Multistage classification by using logistic regression and neural networks for assessment of financial condition of company
B Swiderski, J Kurek, S Osowski
Decision Support Systems 52 (2), 539-547, 2012
492012
Deep learning and non-negative matrix factorization in recognition of mammograms
B Swiderski, J Kurek, S Osowski, M Kruk, W Barhoumi
Eighth International Conference on Graphic and Image Processing (ICGIP 2016 …, 2017
442017
Novel methods of image description and ensemble of classifiers in application to mammogram analysis
B Swiderski, S Osowski, J Kurek, M Kruk, I Lugowska, P Rutkowski, ...
Expert Systems with Applications 81, 67-78, 2017
352017
Developing automatic recognition system of drill wear in standard laminated chipboard drilling process
S Osowski, J Kurek, M Kruk, J Górski, P Hoser, G Wieczorek, A Jegorowa, ...
Bulletin of the Polish Academy of Sciences Technical Sciences, 633-640-633-640, 2016
322016
False-positive reduction in computer-aided mass detection using mammographic texture analysis and classification
S Dhahbi, W Barhoumi, J Kurek, B Swiderski, M Kruk, E Zagrouba
Computer methods and programs in biomedicine 160, 75-83, 2018
302018
Use of nearest neighbors (k-NN) algorithm in tool condition identification in the case of drilling in melamine faced particleboard
A Jegorowa, J Górski, J Kurek, M Kruk
Maderas. Ciencia y tecnología 22 (2), 189-196, 2020
272020
Deep learning versus classical neural approach to mammogram recognition
J Kurek, B Świderski, S Osowski, M Kruk, W Barhoumi
Bulletin of the Polish Academy of Sciences. Technical Sciences 66 (6), 831-840, 2018
272018
Transfer learning in recognition of drill wear using convolutional neural network
J Kurek, G Wieczorek, BSM Kruk, A Jegorowa, S Osowski
2017 18th International Conference on Computational Problems of Electrical …, 2017
272017
Ensemble of classifiers and wavelet transformation for improved recognition of Fuhrman grading in clear-cell renal carcinoma
M Kruk, J Kurek, S Osowski, R Koktysz, B Swiderski, T Markiewicz
Biocybernetics and Biomedical Engineering 37 (3), 357-364, 2017
262017
Initial study on the use of support vector machine (SVM) in tool condition monitoring in chipboard drilling
A Jegorowa, J Górski, J Kurek, M Kruk
European journal of wood and wood products 77, 957-959, 2019
252019
Deep learning in assessment of drill condition on the basis of images of drilled holes
J Kurek, B Swiderski, A Jegorowa, M Kruk, S Osowski
Eighth International Conference on Graphic and Image Processing (ICGIP 2016 …, 2017
252017
Texture characterization based on the Kolmogorov–Smirnov distance
B Swiderski, S Osowski, M Kruk, J Kurek
Expert systems with applications 42 (1), 503-509, 2015
172015
Deep learning methods for drill wear classification based on images of holes drilled in melamine faced chipboard
A Jegorowa, J Kurek, I Antoniuk, W Dołowa, M Bukowski, P Czarniak
Wood Science and Technology 55, 271-293, 2021
152021
Random CNN structure: tool to increase generalization ability in deep learning
B Swiderski, S Osowski, G Gwardys, J Kurek, M Slowinska, I Lugowska
Eurasip journal on image and video processing 2022 (1), 3, 2022
132022
Data augmentation techniques for transfer learning improvement in drill wear classification using convolutional neural network
J Kurek, I Antoniuk, J Górski, A Jegorowa, B Świderski, M Kruk, ...
Machine Graphics and Vision 28, 2019
132019
Application of siamese networks to the recognition of the drill wear state based on images of drilled holes
J Kurek, I Antoniuk, B Świderski, A Jegorowa, M Bukowski
Sensors 20 (23), 6978, 2020
122020
Classifiers ensemble of transfer learning for improved drill wear classification using convolutional neural network
J Kurek, I Antoniuk, J Górski, A Jegorowa, B Świderski, M Kruk, ...
Machine Graphics & Vision 28 (1/4), 2019
122019
Prediction of Blueberry (Vaccinium corymbosum L.) Yield Based on Artificial Intelligence Methods
G Niedbała, J Kurek, B Świderski, T Wojciechowski, I Antoniuk, K Bobran
Agriculture 12 (12), 2089, 2022
112022
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