Institute of Information Theory and Automation

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Bibliography

Conference Paper (international conference)

Sketch2Code: Automatic hand-drawn UI elements detection with Faster R-CNN

Zita Aleš, Picek L., Říha A.

: CEUR Workshop Proceedings : Volume 2696. Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum, 82

: CLEF 2020, (Thessaloniki, GR, 20200922)

: LO1506, GA MŠk

: Computer Vision, Object Detection, Machine Learning

: http://library.utia.cas.cz/separaty/2020/ZOI/zita-0536724.pdf

(eng): 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.\n

: JD

: 20204

2019-01-07 08:39