Convolutional architecture for efficient semantic segmentation of large images
Ova doktorska disertacija proučava primjenu konvolucijskih neuronskih mreža za problem semantičke segmentacije velikih slika. Fokus je na obradi slika pribavljenih iz vozila u pokretu. To predstavlja dodatan izazov jer se objekti pojavljuju na širokom rasponu veličina, a vrlo je važno da metoda radi...
| Permalink: | http://skupnikatalog.nsk.hr/Record/fer.KOHA-OAI-FER:52393/Similar |
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| Glavni autor: | Krešo, Ivan (-) |
| Ostali autori: | Šegvić, Siniša (Thesis advisor) |
| Vrsta građe: | Knjiga |
| Jezik: | eng hrv |
| Impresum: |
Zagreb :
I. Krešo; Faculty of electrical engoneering and computing,
2021.
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APA stil citiranja
Krešo, I., & Šegvić, S. (2021). Convolutional architecture for efficient semantic segmentation of large images: Convolutional architecture for efficient semantic segmentation of large images : doctoral thesis. Zagreb: I. Krešo; Faculty of electrical engoneering and computing.
Chicago stil citiranjaKrešo, Ivan, and Siniša Šegvić. Convolutional architecture for efficient semantic segmentation of large images: Convolutional architecture for efficient semantic segmentation of large images : doctoral thesis. Zagreb: I. Krešo; Faculty of electrical engoneering and computing, 2021.
MLA stil citiranjaKrešo, Ivan, and Siniša Šegvić. Convolutional architecture for efficient semantic segmentation of large images: Convolutional architecture for efficient semantic segmentation of large images : doctoral thesis. Zagreb: I. Krešo; Faculty of electrical engoneering and computing, 2021.