title: Ð Ð°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ Ñ Ð¸Ð¼Ð¸ÑÐµÑÐºÐ¾Ð¹ ÑÑÑÑÐºÑÑÑÑ Ð¼Ð¾Ð»ÐµÐºÑÐ»Ñ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Molecular structure detection by machine learning methods
Creators: name: ÐÐ°Ð¼Ð°ÑÐºÐ¸Ð½ÑÐºÐ¸Ð¹, ÐÐ¾Ð½ÑÑÐ°Ð½ÑÐ¸Ð½
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: ÐÐ°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¥Ð¸Ð¼Ð¸Ñ
Ð·Ð°Ð´Ð°ÑÐ° ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ
object detection

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description: This study aims at building a software product capable of recognizing the structure of chemical molecules, stereoorganic ones in particular. The primary feature of this product is the ability to recognize images from photocopies of print materials and electronic documents. The study involved the analysis of the software products designed to recognize the structure of a molecule, that are based on optical character recognition (algorithmic approach) and machine learning. The solution was developed in the machine learning paradigm, and it included building a pipeline of three machine learning models with the Faster R-CNN, CNN and CNN architectures. A set of InChl sequences used for training and testing models was found in open source. A generator was developed for producing molecule images with various augmentations, such as changing image resolution, varying thickness and length of lines representing the bonds between atoms, atomic label fonts, Gaussian noise. An algorithm was designed to assemble the correctly recognized chemical components into one molecule and then validate the resulting chemical compound. The quality of image recognition and molecule assembly was assessed and compared with the existing solutions. The software product performance was measured and evaluated. The software code is written in the Python programming language. The models were trained on the Google Cloud platform and on personal computer with a GPU.