Zobrazeno 1 - 8
of 8
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).
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)
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
Autor:
PENGZHEN REN1 pzhren@foxmail.com, YUN XIAO1 yxiao@nwu.edu.cn, XIAOJUN CHANG2 xiaojun.chang@rmit.edu.au, PO-YAO HUANG3 poyaoh@andrew.cmu.edu, ZHIHUI LI4 zhihuilics@gmail.com, GUPTA, BRIJ B.5, XIAOJIANG CHEN1, XIN WANG1
Publikováno v:
ACM Computing Surveys. Dec2022, Vol. 54 Issue 9, p1-40. 40p.
Autor:
Michał Choraś, Ryszard S. Choraś
This book presents a selection of high-quality peer-reviewed research papers on various aspects of computer science and networks. It not only discusses emerging applications of currently available solutions, but also outlines potential future techniq
The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43