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Albina Jegorowa (Albina Egorova)
Albina Jegorowa (Albina Egorova)
SGGW w Warszawie, WTD, Katedra mechanicznej obróbki drewna
Geverifieerd e-mailadres voor sggw.pl
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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
362016
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
332020
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
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
292019
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
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
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
172019
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), 13-23, 2019
162019
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
152020
Decision confidence assessment in multi-class classification
M Bukowski, J Kurek, I Antoniuk, A Jegorowa
Sensors 21 (11), 3834, 2021
102021
Tool condition monitoring for the chipboard drilling process using automatic, signal-based tool state evaluation
B Świderski, I Antoniuk, J Kurek, M Bukowski, J Górski, A Jegorowa
BioResources 17 (3), 5349, 2022
82022
Multiclass image classification using gans and cnn based on holes drilled in laminated chipboard
G Wieczorek, M Chlebus, J Gajda, K Chyrowicz, K Kontna, M Korycki, ...
Sensors 21 (23), 8077, 2021
82021
Diagnostic system of drill condition in laminated chipboard drilling process
B Świderski, J Kurek, S Osowski, M Kruk, A Jegorowa
MATEC Web of Conferences 125, 2017
82017
Time-efficient approach to drill condition monitoring based on images of holes drilled in melamine faced chipboard
A Jegorowa, I Antoniuk, J Kurek, M Bukowski, W Dołowa, P Czarniak
BioResources 15 (4), 9611, 2020
62020
The Use of Multilayer Perceptron (MLP) to Reduce Delamination during Drilling into Melamine Faced Chipboard
A Jegorowa, J Kurek, M Kruk, J Górski
Forests 13 (6), 933, 2022
52022
Effect of Nitrogen Ion Implantation on the Tool Life Used in Particleboard CNC Drilling
J Wilkowski, A Jegorowa, M Barlak, Z Werner, J Zagórski, B Staszkiewicz, ...
Materials 15 (10), 3420, 2022
52022
Automatic recognition of drill condition on the basis of images of drilled holes
M Kruk, A Jegorowa, J Kurek, S Osowski, J Gorski
2016 17th International Conference Computational Problems of Electrical …, 2016
52016
Значение виброакустических сигналов таких как вибрация и шум в диагностике износа инструмента во время сверления в древесностружечной ламинированной плите
A JEGOROWA, J GÓRSKI, R MOREK, P PODZIEWSKI, K SZYMANOWSKI, ...
Annals of Warsaw University of Life Sciences–SGGW, Forestry and Wood …, 2015
52015
Automatic identification of drill condition during drilling process in standard laminated chipboard with the use of long short-term memory (LSTM)
J Kurek, G Wieczorek, B Swiderski, M Kruk, A Jegorowa, J Gorski
19th International Conference Computational Problems of Electrical …, 2018
42018
Automatic estimation of drill wear based on images of holes drilled in melamine faced chipboard with machine learning algorithms
A Jegorowa, J Kurek, I Antoniuk, A Krupa, G Wieczorek, B Świderski, ...
Forests 14 (2), 205, 2023
32023
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