Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Krystian Radlak"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-26 (2023)
Abstract In this paper, a novel approach to the mixed Gaussian and impulsive noise reduction in color images is proposed. The described denoising framework is based on the Non-Local Means (NLM) technique, which proved to efficiently suppress only the
Externí odkaz:
https://doaj.org/article/f6c1f567cde94095bfe6f486c80cd7b1
Autor:
Karolina Szczepankiewicz, Adam Popowicz, Kamil Charkiewicz, Katarzyna Nałęcz-Charkiewicz, Michał Szczepankiewicz, Sławomir Lasota, Paweł Zawistowski, Krystian Radlak
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-14 (2023)
Abstract Deep neural networks (DNNs) have achieved outstanding results in domains such as image processing, computer vision, natural language processing and bioinformatics. In recent years, many methods have been proposed that can provide a visual ex
Externí odkaz:
https://doaj.org/article/ac891ea96fa34318aec2041fcf852a11
Autor:
Adam Popowicz, Krystian Radlak, Slawomir Lasota, Karolina Szczepankiewicz, Michal Szczepankiewicz
Publikováno v:
Applied Sciences, Vol 12, Iss 14, p 6842 (2022)
Deep neural networks (DNNs) have been used successfully for many image classification problems. One of the most important factors that determines the final efficiency of a DNN is the correct construction of the training set. Erroneously labeled train
Externí odkaz:
https://doaj.org/article/96477f8b291f48af8ffdc01eaef34a02
Publikováno v:
PLoS ONE, Vol 16, Iss 6, p e0253117 (2021)
The substantial improvement in the efficiency of switching filters, intended for the removal of impulsive noise within color images is described. Numerous noisy pixel detection and replacement techniques are evaluated, where the filtering performance
Externí odkaz:
https://doaj.org/article/4476cacf4e264d8aa25047f7cd59e513
Publikováno v:
Sensors, Vol 20, Iss 10, p 2782 (2020)
Noise reduction is one of the most important and still active research topics in low-level image processing due to its high impact on object detection and scene understanding for computer vision systems. Recently, we observed a substantially increase
Externí odkaz:
https://doaj.org/article/1ac34a033c854ef59f09c79db973e228
Autor:
Adam Popowicz, Krystian Radlak, Slawomir Lasota, Karolina Szczepankiewicz, Michal Szczepankiewicz
Publikováno v:
2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR).
Autor:
Piotr Satala, Krystian Radlak
Publikováno v:
2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR).
Autor:
Michal Szczepankiewicz, Krystian Radlak, Karolina Szczepankiewicz, Adam Popowicz, Pawel Zawistowski
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031148613
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::725b81fa37d26e9605b26cec33b0d13c
https://doi.org/10.1007/978-3-031-14862-0_4
https://doi.org/10.1007/978-3-031-14862-0_4
Autor:
Rainer Faller, Krystian Radlak
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031148613
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e5006c9c9182e7a120c580f4fcf04ad
https://doi.org/10.1007/978-3-031-14862-0_2
https://doi.org/10.1007/978-3-031-14862-0_2
Publikováno v:
Real-Time Image Processing and Deep Learning 2021.
Deep Neural Networks (DNNs) have been deployed in many real-world applications in various domains, both industry and academic, and have proven to deliver outstanding performance. However, DNNs are vulnerable to adversarial attacks, that are small per