Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Szymon Piechaczek"'
Publikováno v:
Sensors, Vol 22, Iss 19, p 7520 (2022)
This paper presents an investigation of the responsivity of a time-delay integration (TDI) charge-coupled device that employs anti-blooming clocking and uses a varying number of TDI stages. The influence of charge blooming caused by unused TDI stages
Externí odkaz:
https://doaj.org/article/1a17f73a2b74479e9739da98673ea8b9
Autor:
Jakub Nalepa, Michal Myller, Jacek Andrzejewski, Pawel Benecki, Szymon Piechaczek, Daniel Kostrzewa
Publikováno v:
Acta Astronautica. 198:689-701
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::994a03dbabadb6f693fe35aabf16edcc
https://doi.org/10.1016/j.actaastro.2022.06.026
https://doi.org/10.1016/j.actaastro.2022.06.026
Publikováno v:
GECCO Companion
Detecting anomalies in telemetry data captured on-board satellites is a pivotal step towards their safe operation. The data-driven algorithms for this task are often heavily parameterized, and the incorrect hyperparameters can deteriorate their perfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d7d034afbb8f23fd7bb430b21aa5e96
https://doi.org/10.1145/3449726.3459411
https://doi.org/10.1145/3449726.3459411
Autor:
Michael P. Hayball, Michal Kawulok, Marcin Cwiek, Pawel Wawrzyniak, Pawel Ulrych, Szymon Piechaczek, Wojciech Dudzik, Janusz Szymanek, M. Marcinkiewicz, Grzegorz Mrukwa, Pablo Ribalta Lorenzo, Barbara Bobek-Billewicz, Jakub Nalepa
Publikováno v:
ICIP
Data augmentation helps improve generalization of deep neural networks, and can be perceived as implicit regularization. It is pivotal in scenarios in which the amount of ground-truth data is limited, and acquiring new examples is costly and time-con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f924af439acd2829bd0dc7b8d0170f68
https://doi.org/10.1109/icip.2019.8803423
https://doi.org/10.1109/icip.2019.8803423
Autor:
Szymon Piechaczek, Krzysztof Hrynczenko, Bogdan Smolka, Michal Kawulok, Jakub Nalepa, Daniel Kostrzewa, Pawel Benecki
Publikováno v:
Real-Time Image Processing and Deep Learning 2019.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::681f767b6a08d743831c4668fee69bf6
https://doi.org/10.1117/12.2519579
https://doi.org/10.1117/12.2519579
Autor:
Szymon Piechaczek, Jakub Nalepa, Daniel Kostrzewa, Michal Kawulok, Pawel Benecki, Krzysztof Hrynczenko
Super-resolution reconstruction (SRR) is a process aimed at enhancing spatial resolution of images, either from a single observation, based on the learned relation between low and high resolution, or from multiple images presenting the same scene. SR
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a7f10b158a95b21c8774df51bdcf74f
http://arxiv.org/abs/1903.00440
http://arxiv.org/abs/1903.00440
Autor:
Szymon Piechaczek, Krzysztof Hrynczenko, Jakub Nalepa, Daniel Kostrzewa, Michal Kawulok, Pawel Benecki
Publikováno v:
Beyond Databases, Architectures and Structures. Paving the Road to Smart Data Processing and Analysis ISBN: 9783030190927
BDAS
BDAS
Super-resolution reconstruction (SRR) is aimed at increasing image spatial resolution from multiple images presenting the same scene or from a single image based on the learned relation between low and high resolution. Emergence of deep learning allo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5a508a3eae31fafb04ad897e8e257f1
https://doi.org/10.1007/978-3-030-19093-4_16
https://doi.org/10.1007/978-3-030-19093-4_16
Autor:
Jakub Nalepa, Szymon Piechaczek, Daniel Kostrzewa, Michal Kawulok, Pawel Benecki, Krzysztof Hrynczenko
Publikováno v:
IGARSS
The capabilities of super-resolution reconstruction (SRR)---techniques for enhancing image spatial resolution---have been recently improved significantly by the use of deep convolutional neural networks. Commonly, such networks are learned using huge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e9d9b016dcedb65e8f56b86979e301a
Publikováno v:
Applications of Evolutionary Computation ISBN: 9783030166915
EvoApplications
EvoApplications
Creating classification ensembles may be perceived as a regularization technique which aims at improving the generalization capabilities of a classifier. In this paper, we introduce a multi-level memetic algorithm for evolving classification ensemble
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0d4623f040189e19ad66d77ffb8acb8
https://doi.org/10.1007/978-3-030-16692-2_20
https://doi.org/10.1007/978-3-030-16692-2_20
Publikováno v:
Advances in Intelligent Networking and Collaborative Systems ISBN: 9783319985565
INCoS
INCoS
Breast cancer is the most pervasive form of cancers in women, therefore automated algorithms for cancer detection, and analysis of hematoxylin and eosin stained breast-cancer histopathology images are being actively developed worldwide. In this paper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::84ab6818166df577a0d52d3ab00ed26a
https://doi.org/10.1007/978-3-319-98557-2_49
https://doi.org/10.1007/978-3-319-98557-2_49