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pro vyhledávání: '"Szabó, Gergely"'
The accurate tracking of live cells using video microscopy recordings remains a challenging task for popular state-of-the-art image processing based object tracking methods. In recent years, several existing and new applications have attempted to int
Externí odkaz:
http://arxiv.org/abs/2308.03887
Autor:
Gengo, Rafaela Machado, Louro, Vinicius Hector Abud, Moraes, Renato, Szabó, Gergely Andres Julio, Dantas, Elton Luiz, Simões, Pedro Machado
Publikováno v:
In Journal of South American Earth Sciences 15 November 2024 148
Publikováno v:
In Journal of Psychiatric Research September 2024 177:271-278
Autor:
Szabo, Gergely, Horvath, Andras
Convolutional networks are considered shift invariant, but it was demonstrated that their response may vary according to the exact location of the objects. In this paper we will demonstrate that most commonly investigated datasets have a bias, where
Externí odkaz:
http://arxiv.org/abs/2112.09195
Autor:
Szabó, Loránd, Bertalan, László, Szabó, Gergely, Grigorszky, István, Somlyai, Imre, Dévai, György, Nagy, Sándor Alex, Holb, Imre J., Szabó, Szilárd
Publikováno v:
In Ecological Informatics July 2024 81
The pooling operation is a cornerstone element of convolutional neural networks. These elements generate receptive fields for neurons, in which local perturbations should have minimal effect on the output activations, increasing robustness and invari
Externí odkaz:
http://arxiv.org/abs/2011.00869
Akademický článek
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Autor:
Gengo, Rafaela Machado, Moraes, Renato, Batista, Laísa de Assis, Santos, Caio Arthur, Szabó, Gergely Andres Julio
Publikováno v:
In LITHOS 1 November 2023 456-457
Autor:
Konkolÿ Thege, Barna, Moore, Annabelle, Szabó, Gergely S., Fitzgerald, Michael, Hodgins, David C., Kim, Hyoun S.
Publikováno v:
In Psychiatry Research October 2023 328
Autor:
Bátfai, Norbert, Papp, Dávid, Bogacsovics, Gergő, Szabó, Máté, Simkó, Viktor Szilárd, Bersenszki, Márió, Szabó, Gergely, Kovács, Lajos, Kovács, Ferencz, Varga, Erik Szilveszter
In this paper, we performed two types of software experiments to study the numerosity classification (subitizing) in humans and machines. Experiments focus on a particular kind of task is referred to as Semantic MNIST or simply SMNIST where the numer
Externí odkaz:
http://arxiv.org/abs/1906.12213