Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Agnieszka Dąbrowska-Boruch"'
Autor:
Jakub Caputa, Maciej Wielgosz, Daria Łukasik, Paweł Russek, Jakub Grzeszczyk, Michał Karwatowski, Szymon Mazurek, Rafał Frączek, Anna Śmiech, Ernest Jamro, Sebastian Koryciak, Agnieszka Dąbrowska-Boruch, Marcin Pietroń, Kazimierz Wiatr
Publikováno v:
Life, Vol 14, Iss 3, p 321 (2024)
The primary objective of this research was to enhance the quality of semantic segmentation in cytology images by incorporating super-resolution (SR) architectures. An additional contribution was the development of a novel dataset aimed at improving i
Externí odkaz:
https://doaj.org/article/aefea36f497b4297bc0579db5d4342e1
Autor:
Szymon Mazurek, Maciej Wielgosz, Jakub Caputa, Rafał Frączek, Michał Karwatowski, Jakub Grzeszczyk, Daria Łukasik, Anna Śmiech, Paweł Russek, Ernest Jamro, Agnieszka Dąbrowska-Boruch, Marcin Pietroń, Sebastian Koryciak, Kazimierz Wiatr
Publikováno v:
Annals of Computer Science and Information Systems.
Publikováno v:
Electronics
Volume 10
Issue 20
Electronics, Vol 10, Iss 2505, p 2505 (2021)
Volume 10
Issue 20
Electronics, Vol 10, Iss 2505, p 2505 (2021)
Testing FPGA-based soft processor cores requires a completely different methodology in comparison to standard processors. The stuck-at fault model is insufficient, as the logic is implemented by lookup tables (LUTs) in FPGA, and this SRAM-based LUT m
This paper describes a new optimization methodology of testing vector sets reduction for testing of soft-processor cores and their individual blocks. The deterministic test vectors both for whole core and its individual blocks are investigated that s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4679aaf1616f7814bb86102d2df52f4a
Publikováno v:
The International Journal of High Performance Computing Applications. 34:103-114
In this article, we study the steepest descent local search (SDLS) algorithm that is used as the improvement step in the memetic algorithms for the search of low autocorrelation binary sequences (LABS). We address the method of reconfigurable computi
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319562575
ARC
ARC
In this paper, we present the Arbitrary Precision Arithmetic Library - ArPALib, suitable for algorithms that require integer data representation with an arbitrary bit-width (up to 4096-bit in this study). The unique feature of the library is suitabil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb202b67ddebd3c1dce9b6fb477604c2
https://doi.org/10.1007/978-3-319-56258-2_28
https://doi.org/10.1007/978-3-319-56258-2_28
Publikováno v:
Image Processing & Communications. 19:15-23
In this paper an implementation of the module responsible for the control of micro-mirror array for later use in projection is described. Existing technologies allow for projections of medical images in Digital Imaging and Communications in Medicine
Publikováno v:
ipc. 17:103-108
Many algorithms are used in JPEG standard for compression of still images, but the most demanding one is the DCT. The fast discrete cosine transform is the basic transform which occur in most coding algorithms. In the case of images it is performed o
Publikováno v:
COMPUTING AND INFORMATICS; Vol 32, No 6 (2013): Computing and Informatics; 1272-1292
Monte Carlo simulations are widely used e.g. in the field of physics and molecular modelling. The main role played in these is by the high performance random number generators, such as RANLUX or MERSSENE TWISTER. In this paper the authors introduce t
Autor:
Agnieszka Dąbrowska-Boruch, Ernest Jamro, Marcin Janiszewski, Dawid Kuna, Krzysztof Machaczek, Paweł Russek, Kazimierz Wiatr, Maciej Wielgosz
The primary intention of this paper is to present the results of several cases where the FPGA technology was used for high performance calculations. We gathered applications that had been developed over the last couple of years. Over this period of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a3e3a8ca6ed374d3a1cfba92e497f584