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of 3 397
pro vyhledávání: '"gradient noise"'
Akademický článek
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Publikováno v:
Надежность и качество сложных систем, Iss 2 (2022)
Background. Scientific article reveals the problem of analyzing, recognizing and managing highdefinition images with a minimum error due to the previous frame-by-frame recognition of a complex of lowdefinition images. The fundamental problem is the
Externí odkaz:
https://doaj.org/article/15a9f3247a174c0f9e0d5b4e6d77e93f
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 1, Pp 28-45 (2020)
This paper formulates a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. The smoothness condition softens the
Externí odkaz:
https://doaj.org/article/a0cd13ef360445e2a0bcc361cb2c396c
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 1, Pp 46-63 (2020)
Part I of this paper formulated a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. A diffusion strategy was d
Externí odkaz:
https://doaj.org/article/f8824f76f61a4132b8ab62fa83f4145d
Publikováno v:
Neurocomputing. 490:206-216
In recent years, many interpretable methods based on class activation maps (CAMs) have served as an important judging basis for the predictions of convolutional neural networks (CNNs). However, these methods still suffer from the problems of gradient
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::508baeff1d71f71618754c1cc02438aa
https://doi.org/10.1016/j.neucom.2021.11.084
https://doi.org/10.1016/j.neucom.2021.11.084
Publikováno v:
Computational Visual Media. 7:349-362
Procedural noise functions are fundamental tools in computer graphics used for synthesizing virtual geometry and texture patterns. Ideally, a procedural noise function should be compact, aperiodic, parameterized, and randomly accessible. Traditional
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15323d315b281f9c1df5c42efe98a801
https://doi.org/10.1007/s41095-021-0206-z
https://doi.org/10.1007/s41095-021-0206-z
Publikováno v:
IEEE Open Journal of Signal Processing
IEEE Open Journal of Signal Processing, IEEE, 2020, 1, pp.46-63. ⟨10.1109/ojsp.2020.2989031⟩
IEEE Open Journal of Signal Processing, IEEE, 2020, 1, pp.46-63. ⟨10.1109/ojsp.2020.2989031⟩
International audience; Part I of this paper formulated a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00016593d6dbbe5ea0028dd693de0fa2
https://doi.org/10.1109/ojsp.2020.2989031
https://doi.org/10.1109/ojsp.2020.2989031
Autor:
Prabhishek Singh, Raj Shree
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 32, Iss 1, Pp 137-148 (2020)
In synthetic aperture radar (SAR) images, degradation due to multiplicative speckle noise and detail blurring is one of the common problem. This problem is solved by despeckling method. The main objective of image despeckling is to eliminate the spec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::604f28e10d9969ba7b04d570899d66a6
http://www.sciencedirect.com/science/article/pii/S1319157817301106
http://www.sciencedirect.com/science/article/pii/S1319157817301106
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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Publikováno v:
Signal Processing. 165:1-6
The shrinkage widely linear complex-valued least mean square (SWL-CLMS) algorithm with a variable step-size (VSS) overcomes the tradeoff between fast convergence and low steady-state misalignment, but meanwhile suffers from instability for highly cor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd9c97aab94a5e4512eaf84cd97ba641
https://doi.org/10.1016/j.sigpro.2019.06.029
https://doi.org/10.1016/j.sigpro.2019.06.029