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DOI: 10.1109/SLT.2016.7846296 1 10.1109/SLT.2016.7846296 false true Reference 31876426 /api/reference/31876426 2. DOI: 10.1109/IWQoS.2018.8624183 2 10.1109/IWQoS.2018.8624183 false true Reference 31876427 /api/reference/31876427 3. goodfellow 2016: Deep Learning 3 false true Reference 31876428 /api/reference/31876428 4. krizhevsky 2012: Learning Multiple Layers of Features from Tiny Images., Journal of Software Engineering and Applications, 11 4 false true Reference 31876429 /api/reference/31876429 5. barreto 0: Neural Network Architecture. 5 false true Reference 31876430 /api/reference/31876430 6. 2020: Bean disease dataset 6 false true Reference 31876431 /api/reference/31876431 7. sandler 2018: Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification., CoRR 7 false true Reference 31876432 /api/reference/31876432 8. khosla 2011: Novel dataset for Fine-Grained Image Categorization. First Workshop on Fine-Grained Visual Categorization (FGVC)., IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 8 false true Reference 31876433 /api/reference/31876433 9. DOI: 10.1109/CVPR.2016.308 9 10.1109/CVPR.2016.308 false true Reference 31876434 /api/reference/31876434 10. DOI: 10.12700/APH.18.5.2021.5.3 10 10.12700/APH.18.5.2021.5.3 false true Reference 31876435 /api/reference/31876435 11. DOI: 10.1007/s12530-020-09345-2 11 10.1007/s12530-020-09345-2 false true Reference 31876436 /api/reference/31876436 12. DOI: 10.1002/widm.1301 12 10.1002/widm.1301 false true Reference 31876437 /api/reference/31876437 13. kanade 2020: Machine learning model for stock market prediction., International Journal of Applied Science and Engineering Research, 8, p. 209 13 false true Reference 31876438 /api/reference/31876438 14. DOI: 10.1109/ICHI.2018.00095 14 10.1109/ICHI.2018.00095 false true Reference 31876439 /api/reference/31876439 15. DOI: 10.1109/SSCI44817.2019.9002720 15 10.1109/SSCI44817.2019.9002720 false true Reference 31876440 /api/reference/31876440 16. DOI: 10.1109/ACCESS.2022.3140513 16 10.1109/ACCESS.2022.3140513 false true Reference 31876441 /api/reference/31876441 17. DOI: 10.1007/s11263-015-0816-y 17 10.1007/s11263-015-0816-y false true Reference 31876442 /api/reference/31876442 18. charrez 2019: Neurips 2019 Stats 18 false true Reference 31876443 /api/reference/31876443 19. DOI: 10.1109/ICICIS46948.2019.9014658 19 10.1109/ICICIS46948.2019.9014658 false true Reference 31876444 /api/reference/31876444 20. DOI: 10.12700/APH.18.3.2021.3.13 20 10.12700/APH.18.3.2021.3.13 false true Reference 31876445 /api/reference/31876445 21. DOI: 10.1109/TMRB.2019.2913282 21 10.1109/TMRB.2019.2913282 false true Reference 31876446 /api/reference/31876446 22. DOI: 10.12700/APH.17.2.2020.2.11 22 10.12700/APH.17.2.2020.2.11 false true /api/publication/32907752 Barreto Saulo Cardoso et al. Training and Analysis of Hyperparameters in Neural Networks for Computer Vision Applications: A Didactic Approach. (2022) Megjelent: IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and Informatics SAMI (2022) pp. 383-388<div class="BookChapter Publication long-list"> <div class="authors"> <img title="Forrásközlemény" style="float: left" src="/frontend/resources/grid/publication-core-icon.png"> <img title="Idézőközlemény" style="float: left" src="/frontend/resources/grid/publication-citation-icon.png"> <div class="autype autype0"> <span class="author-name" >Barreto Saulo Cardoso </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10021940"><a href="/gui2/?type=authors&mode=browse&sel=10021940" target="_blank">Szemes Peter Tamas (<span class="authorship-author-name">Szemes Péter Tamás</span> <span class="authorAux-mtmt"> Robotika, vezeték nélküli szenzorhálózatok</span>) </a> </span> <span class="author-affil"><span title="Debreceni Egyetem">DE</span>/<span title="Műszaki Kar">MK</span>/Mechatronikai Tanszék</span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;32907752" target="_blank">Training and Analysis of Hyperparameters in Neural Networks for Computer Vision Applications : A Didactic Approach.</a></div> <div class="InBook"><div class="chapter-in">In:</div> <div class="authors"> <div class="autype autype-1"> <span class="author-affil">IEEE</span> (szerk.) </div> </div> <div class="booktitle"><a href="/gui2/?mode=browse&params=publication;32596945" target="_blank">IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and Informatics SAMI (2022) : Proceedings </a></div> <div class="conference"> Konferencia helye, ideje: <span class="location">Poprad, Szlovákia <span class="conference-date">2022.03.02. - 2022.03.05.</span> </div> <span class="publishedAt">Poprad: <span class="publishers">Institute of Electrical and Electronics Engineers (IEEE)</span>, <span class="page"> pp 383-388 </span> <span class="year">(2022)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Nyelv: Angol | </span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="10.1109/SAMI54271.2022.9780769" target="_blank" href="https://doi.org/10.1109/SAMI54271.2022.9780769"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="9780769" target="_blank" href="http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=9780769"> IEEE Xplore </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="343790" target="_blank" href="http://hdl.handle.net/2437/343790"> DEA </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="85132135827" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85132135827"> Scopus </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:black" title="https://ieeexplore.ieee.org/document/9780769/" target="_blank" href="https://ieeexplore.ieee.org/document/9780769/"> Egyéb URL </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="ukflPbcpxNEJ" target="_blank" href="http://scholar.Google.com/scholar?hl=en&lr=&cluster=ukflPbcpxNEJ"> Google scholar </a> </span> </span> <span class="bookchapter-ids">Befoglaló link(ek):</span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <span class="isbnOrIssn"> ISBN: </span> <a style="color:black" title="9781665497046" target="_blank" href="https://www.worldcat.org/search?q=isbn%3A9781665497046"> 9781665497046 </a> </span> <span class="id identifier oa_none" title="none"> <span class="isbnOrIssn"> ISBN: </span> <a style="color:black" title="9781665497039" target="_blank" href="https://www.worldcat.org/search?q=isbn%3A9781665497039"> 9781665497039 </a> </span> </span> <div class="publication-citation" style="margin-left: 0.5cm;"> <span title="Nyilvános idézőközlemények összesen, említések nélkül" class="citingPub-count">Nyilvános idéző összesen: 3</span> | Független: 2 | Függő: 1 | Nem jelölt: 0 | WoS jelölt: 2 | Scopus jelölt:&nbsp;3 | WoS/Scopus jelölt:&nbsp;3 | DOI jelölt:&nbsp;3 </div> <div class="publication-citation"> <a target="_blank" href="/api/publication?cond=citations.related;eq;32907752&sort=publishedYear,desc&sort=title"> Idézett közlemények száma: 3 </a> </div> <div class="mtid"><span class="long-pub-mtid">Közlemény: 32907752</span> | <span class="status-data status-APPROVED"> Nyilvános </span> <span class="long-book-mtid">Befoglaló: 32596945</span> Forrás Idéző | <span class="type-subtype">Könyvrészlet ( Konferenciaközlemény ) </span> | <span class="pub-category">Tudományos</span> | <span class="publication-sourceOfData">kézi felvitel</span> </div> <div class="lastModified">Utolsó módosítás: 2023.01.25. 10:48 Kériné Tornyi Katalin (DE 5 admin) </div> </div> </div>