Sketch2Code: Automatic hand-drawn UIelements detection with Faster R-CNN
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43959883" target="_blank" >RIV/49777513:23520/20:43959883 - isvavai.cz</a>
Alternative codes found
RIV/67985556:_____/20:00536724
Result on the web
<a href="http://ceur-ws.org/Vol-2696/paper_82.pdf" target="_blank" >http://ceur-ws.org/Vol-2696/paper_82.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Sketch2Code: Automatic hand-drawn UIelements detection with Faster R-CNN
Original language description
Transcription of User Interface (UI) elements hand drawings to the computer code is a tedious and repetitive task. Therefore, a need arose to create a system capable of automating such process. This paper describes a deep learning-based method for hand-drawn user interface elements detection and localization. The proposed method scored 1st place in the ImageCLEFdrawnUI competition while achieving an overall precision of 0.9708. The final method is based on Faster R-CNN object detector framework with ResNet-50 backbone architecture trained with advanced regularization techniques. The code has been made available at: https://github.com/picekl/ImageCLEF2020-DrawnUI.
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
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
CEUR Workshop proceedings - CLEF 2020 Working Notes
ISBN
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ISSN
1613-0073
e-ISSN
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Number of pages
9
Pages from-to
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Publisher name
CEUR-WS
Place of publication
Thessaloniki
Event location
Thessaloniki, Greece
Event date
Sep 22, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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