Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Attila Tiba"'
Publikováno v:
Mathematics, Vol 12, Iss 12, p 1814 (2024)
In recent years, convolutional neural networks (CNNs) have emerged as highly efficient architectures for image and audio classification tasks, gaining widespread adoption in state-of-the-art methodologies. While CNNs excel in machine learning scenari
Externí odkaz:
https://doaj.org/article/b82771c911b04758a8a2d5dc1670bea8
Autor:
Róbert Lakatos, Gergő Bogacsovics, Balázs Harangi, István Lakatos, Attila Tiba, János Tóth, Marianna Szabó, András Hajdu
Publikováno v:
Big Data and Cognitive Computing, Vol 8, Iss 3, p 20 (2024)
The efficiency of natural language processing has improved dramatically with the advent of machine learning models, particularly neural network-based solutions. However, some tasks are still challenging, especially when considering specific domains.
Externí odkaz:
https://doaj.org/article/2c7c19d602124286a907abca470f4f56
Autor:
Gergő Bogacsovics, András Hajdu, Balázs Harangi, István Lakatos, Róbert Lakatos, Marianna Szabó, Attila Tiba, János Tóth
Publikováno v:
KözigazgatásTudomány, Vol 1, Iss 2, Pp 134-145 (2021)
The world's appetite for energy and minerals seems insatiable. At the current rate of exploitation of the Earth's natural reserves of fossil fuels, humanity could face severe energy shortage problems in the coming decades. We must therefore turn our
Externí odkaz:
https://doaj.org/article/2c1941b1574b415c9f934c7e7622ce5c
Autor:
Gergő Bogacsovics, András Hajdu, Balázs Harangi, István Lakatos, Róbert Lakatos, Marianna Szabó, Attila Tiba, János Tóth, Ádám Tarcsi
Publikováno v:
KözigazgatásTudomány, Vol 1, Iss 2, Pp 146-158 (2021)
The leap forward in artificial intelligence over the last decade, with the continued expansion of the hardware and software platforms that support it, has also taken data analytics to a new level. In principle, this is best understood as a reduction
Externí odkaz:
https://doaj.org/article/3e92b7a835204d6ab64609bb081b1325
Autor:
László Róbert Kolozsvári, Tamás Bérczes, András Hajdu, Rudolf Gesztelyi, Attila Tiba, Imre Varga, Ala'a B. Al-Tammemi, Gergő József Szőllősi, Szilvia Harsányi, Szabolcs Garbóczy, Judit Zsuga
Publikováno v:
Informatics in Medicine Unlocked, Vol 25, Iss , Pp 100691- (2021)
Objectives: The COVID-19 pandemic is considered a major threat to global public health. The aim of our study was to use the official epidemiological data to forecast the epidemic curves (daily new cases) of the COVID-19 using Artificial Intelligence
Externí odkaz:
https://doaj.org/article/a081de2f0be04a5a9e38cc7c55b88847
Autor:
Róbert Lakatos, Attila Tiba, Gergő Bogacsovics, Henrietta Toman, Marcell Beregi-Kovács, Andras Hajdu
Publikováno v:
Annales Mathematicae et Informaticae. 53:73-91
Researchers often use theoretical models which provide a relatively sim- ple, yet concise and effective way of modelling various phenomena. However, it is a well-known fact that the more complex the model, the more complex the mathematical descriptio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3c112e079c75df6979d6b07c4b8517a
https://doi.org/10.33039/ami.2021.02.003
https://doi.org/10.33039/ami.2021.02.003
Publikováno v:
Annales Mathematicae et Informaticae. 53:219-234
Convolutional Neural Network (CNN) for medical image classification has produced satisfying work [11, 12, 15]. Several pretrained models such as VGG19 [17], InceptionV3 [18], and MobileNet [8] are architectures that can be relied on to design high ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a558afecf9acc45851c85b8d8b93fcfe
https://doi.org/10.33039/ami.2021.04.001
https://doi.org/10.33039/ami.2021.04.001
Autor:
Csaba, Bankó, Zsolt László, Nagy, Miklós, Nagy, Gábor György, Szemán-Nagy, István, Rebenku, László, Imre, Attila, Tiba, András, Hajdu, János, Szöllősi, Sándor, Kéki, Zsolt, Bacso
Publikováno v:
Cancers
Volume 13
Issue 22
Cancers, Vol 13, Iss 5652, p 5652 (2021)
Volume 13
Issue 22
Cancers, Vol 13, Iss 5652, p 5652 (2021)
Simple Summary Aside from tissue cell renewal, tumor cells are also produced every day. In ordinary conditions, immunologically controlled cell death mechanisms limit cancer development. There are several cell death processes used for how normal and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::5d95fa757373e72f6a67baa5c29a552d
Publikováno v:
Annales Mathematicae et Informaticae.
In this work, we investigated the ability of several Convolutional Neural Network (CNN) models for predicting the spread of cancer using medical images. We used a dataset released by the Kaggle, namely PatchCamelyon. The dataset consists of 220,025 p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c4f3e242dbff7869fce97dc437616ac
https://doi.org/10.33039/ami.2021.03.013
https://doi.org/10.33039/ami.2021.03.013
Autor:
Judit Zsuga, Szabolcs Garbóczy, Ala’a B. Al-Tammemi, Andras Hajdu, Szilvia Harsányi, László Róbert Kolozsvári, Attila Tiba, Rudolf Gesztelyi, Tamás Bérczes, Gergő József Szőllősi, Imre Varga
Publikováno v:
Informatics in Medicine Unlocked, Vol 25, Iss, Pp 100691-(2021)
Informatics in Medicine Unlocked
Informatics in Medicine Unlocked
Objectives The COVID-19 pandemic is considered a major threat to global public health. The aim of our study was to use the official epidemiological data to forecast the epidemic curves (daily new cases) of the COVID-19 using Artificial Intelligence (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4df3c516793859aac79e10f1e8b3cf3
http://www.sciencedirect.com/science/article/pii/S2352914821001751
http://www.sciencedirect.com/science/article/pii/S2352914821001751