Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Andrzej Bukala"'
Autor:
Marcin Szczuka, Andrzej Janusz, Boguslaw Cyganek, Jakub Grabek, Lukasz Przebinda, Andzelika Zalewska, Andrzej Bukala, Dominik Slezak
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2522d8e26dc3d9f6cb78eae918c54416
https://doi.org/10.1109/bigdata55660.2022.10020599
https://doi.org/10.1109/bigdata55660.2022.10020599
Autor:
Michał Koziarski, Bogusław Cyganek, Przemysław Niedziela, Bogusław Olborski, Zbigniew Antosz, Marcin Żydak, Bogdan Kwolek, Paweł Wąsowicz, Andrzej Bukała, Jakub Swadźba, Piotr Sitkowski
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Cancer diseases constitute one of the most significant societal challenges. In this paper, we introduce a novel histopathological dataset for prostate cancer detection. The proposed dataset, consisting of over 2.6 million tissue patches extr
Externí odkaz:
https://doaj.org/article/f23b38eb892e4544bb6a7917499a9e16
Publikováno v:
BPP_AGH
Journal of Universal Computer Science, Vol 26, Iss 4, Pp 454-478 (2020)
JUCS-Journal of Universal Computer Science 26(4): 454-478
Journal of Universal Computer Science, Vol 26, Iss 4, Pp 454-478 (2020)
JUCS-Journal of Universal Computer Science 26(4): 454-478
Histograms of oriented gradients (HOG) are still one of the most frequently used low-level features for pattern recognition in images. Despite their great popularity and simple implementation performance of the HOG features almost always has been mea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3cad2eee59596bfcab249a83156d6778
https://zenodo.org/record/5508515
https://zenodo.org/record/5508515
Autor:
Zbigniew Antosz, Bogdan Kwolek, Boguslaw Olborski, Michał Koziarski, Bogusław Cyganek, Piotr Sitkowski, Andrzej Bukala, Jakub Swadzba
Publikováno v:
VISIGRAPP (5: VISAPP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0226514e7414f6003d5c21b9f2aea0e
https://doi.org/10.5220/0009163405060512
https://doi.org/10.5220/0009163405060512
Publikováno v:
Image Processing and Communications ISBN: 9783030312534
IP&C
IP&C
While most existing image recognition benchmarks consist of relatively high quality data, in the practical applications images can be affected by various types of distortions. In this paper we experimentally evaluate the extent to which image distort
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6034ef64aa966d66607efb4979121496
https://doi.org/10.1007/978-3-030-31254-1_21
https://doi.org/10.1007/978-3-030-31254-1_21
Autor:
Bogdan Kwolek, Boguslaw Olborski, Zbigniew Antosz, Paweł Wąsowicz, Bogusław Cyganek, Michał Koziarski, Andrzej Bukala, Jakub Swadźba
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions ISBN: 9783030304928
ICANN (Workshop)
ICANN (Workshop)
In this work, we propose an algorithm for training deep neural networks for classification of breast cancer in histopathological images affected by data unbalance with support of active learning. The output of the neural network on unlabeled samples
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8786362c2be7ddf905a2951c206ff7c3
https://doi.org/10.1007/978-3-030-30493-5_31
https://doi.org/10.1007/978-3-030-30493-5_31
Publikováno v:
Journal of Universal Computer Science, Vol 26, Iss 4, Pp 454-478 (2020)
Histograms of oriented gradients (HOG) are still one of the most frequently used low-level features for pattern recognition in images. Despite their great popularity and simple implementation performance of the HOG features almost always has been mea
Externí odkaz:
https://doaj.org/article/93814427fd3c44da812782ca6aad5b7e