Volgen
Michał Kruk
Michał Kruk
sggw
Geverifieerd e-mailadres voor iem.pw.edu.pl
Titel
Geciteerd door
Geciteerd door
Jaar
Melanoma recognition using extended set of descriptors and classifiers
Kruk Michał, Świderski Bartosz, Osowski Stanisław, Kurek Jarosław, Słowińska ...
EURASIP Journal on Image and Video Processing, 2015
492015
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
372017
Developing automatic recognition system of drill wear in standard laminated chipboard drilling process
J Kurek, M Kruk, S Osowski, P Hoser, G Wieczorek, A Jegorowa, J Górski, ...
Bulletin of the Polish Academy of Sciences Technical Sciences 64 (3), 633-640, 2016
352016
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), 2020
312020
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
312018
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
302017
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), 2018
292018
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, 1-3, 2019
272019
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
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
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
182021
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
182015
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 & Vision 28, 2019
162019
Automatic recognition of industrial tools using artificial intelligence approach
T Les, M Kruk, S Osowski
Expert Systems with Applications 40 (12), 4777-4784, 2013
162013
Recognition and classification of colon cells applying the ensemble of classifiers
M Kruk, S Osowski, R Koktysz
Computers in biology and medicine 39 (2), 156-165, 2009
162009
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, 2019
152019
Computerized classification system for the identification of soil microorganisms
M Kruk, R Kozera, S Osowski, P Trzciński, LS Paszt, B Sumorok, ...
AIP Conference Proceedings 1648 (1), 660018, 2015
142015
Aggregation of classifiers ensemble using local discriminatory power and quantiles
B Swiderski, S Osowski, M Kruk, W Barhoumi
Expert Systems with Applications 46, 316-323, 2016
132016
Metody sztucznej inteligencji do wspomagania diagnostyki patologii tkanek
KW OSOWSKI Stanisław, MARKIEWICZ Tomasz, KRUK Michał
Metrologia w medycynie. Wybrane zagadnienia, 91-126, 2011
13*2011
Het systeem kan de bewerking nu niet uitvoeren. Probeer het later opnieuw.
Artikelen 1–20