@inproceedings{c93b1a3587fd4a6dbe32e5283e4349c8,
title = "Widget detection on screenshots using computer vision and machine learning algorithms",
abstract = "In this paper we consider the problem of detecting and recognizing widgets in screenshots of computer programs' graphical user interface (GUI). This problem is fundamental in business process automation. The solution we propose here is based on detecting GUI elements with Canny edge operator, and recognizing already detected GUI elements with classifiers: neural networks, random forests, XGBoost, and others.",
keywords = "GUI decomposition, edge detection, image recognition, machine learning, neural networks, widget detection",
author = "Kacper Radzikowski and Karol Chȩci{\'n}ski and Mateusz Forc and {\L}ukasz Lepak and Micha{\l} Jab{\l}o{\'n}ski and Wiktor Ku{\'s}mirek and Bart{\l}omiej Twardowski and Pawe{\l} Wawrzy{\'n}ski and Nowak, {Robert M.}",
note = "Funding Information: This work was supported by the statutory funds of Institute of Computer Science of Warsaw University of Technology and grant funded by MakeitRight Ltd. We would like to thank all MakeItRight staff that support our work, especially Mr Grzegorz Kozio{\l} who leads the project from MakeItRight side. Publisher Copyright: {\textcopyright} 2019 SPIE.; Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019 ; Conference date: 26-05-2019 Through 02-06-2019",
year = "2019",
doi = "10.1117/12.2536406",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Romaniuk, {Ryszard S.} and Maciej Linczuk",
booktitle = "Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019",
}