Impact of loss function on multi-frame super-resolution
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F21%3APU140865" target="_blank" >RIV/00216305:26220/21:PU140865 - isvavai.cz</a>
Result on the web
<a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2021_sbornik_1.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2021_sbornik_1.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Impact of loss function on multi-frame super-resolution
Original language description
Nowadays, one of the most popular topics in image processing is super-resolution. This problem is getting more actual even in security, since monitoring cameras are everywhere and in the case of an incident, it is necessary to recognize a person from records. A lot of approaches exist, which are able to reconstruct image, and the most of them are based on deep learning. The main focus of this work is to analyze, which loss function for neural networks is more effective for real-world image reconstruction. For this experiment chosen architecture and dataset are used for multi-frame super-resolution for 8 scaling.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings I of the 27th Conference STUDENT EEICT 2021: General papers
ISBN
978-80-214-5942-7
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
601-605
Publisher name
Brno University of Technology, Faculty of Electrical Engineering and Communication
Place of publication
Brno
Event location
Brno
Event date
Apr 27, 2021
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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