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arXiv 2021年

作者： Nurseitov, Daniyar Bostanbekov, Kairat Kanatov, Maksat Alimova, Anel Abdallah, Abdelrahman Abdimanap, Galymzhan Satbayev University Almaty Kazakhstan National Open Research Laboratory for Information and Space Technologies Almaty Kazakhstan MSc Machine Learning & Data Science Satbayev University Almaty Kazakhstan

This article discusses the problem of handwriting recognition in Kazakh and Russian languages. This area is poorly studied since in the literature there are almost no works in this direction. We have tried to describe various approaches and achievements of recent years in the development of handwritten recognition models in relation to Cyrillic graphics. The first model uses deep convolutional neural networks (CNNs) for feature extraction and a fully connected multilayer perceptron neural network (MLP) for word classification. The second model, called SimpleHTR, uses CNN and recurrent neural network (RNN) layers to extract information from images. We also proposed the Bluechet and Puchserver models to compare the results. Due to the lack of available open datasets in Russian and Kazakh languages, we carried out work to collect data that included handwritten names of countries and cities from 42 different Cyrillic words, written more than 500 times in different handwriting. We also used a handwritten database of Kazakh and Russian languages (HKR). This is a new database of Cyrillic words (not only countries and cities) for the Russian and Kazakh languages, created by the authors of this work. © 2021, CC BY.

关键词： Recurrent neural networks

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Automated question-answer medical model based on deep learning technology 20

Automated question-answer medical model based on deep learni...

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6th International Conference on Engineering and MIS, ICEMIS 2020

作者： Abdallah, Abdelrahman Kasem, Mahmoud Hamada, Mohamed A. Sdeek, Shaymaa MSc Machine Learning and Data Science Satbayev University Almaty Kazakhstan Information Technology Assiut University Assiut Egypt IS Department International IT University Almaty Kazakhstan Dept. Information System Assiut University Qena Egypt

ISBN: (纸本)9781450377362

Artificial intelligence can now provide more solutions for different problems, especially in the medical field. One of those problems is the lack of answers to any given medical/health-related question. The Internet is full of forums that allow people to ask some specific questions and get great answers for them. Nevertheless, browsing these questions to locate a similar case to your own question, also finding a satisfying accurate answer is difficult and timeconsuming task. This research will introduce a solution to these problems by automating the process of generating qualified answers to these questions and creating a kind of digital doctor. Furthermore, this research will train an end-to-end model using the framework of RNN and the encoder decoder to generate sensible and useful answers to a small set of medical/health issues. The proposed model was trained and evaluated using data from various online services, such as WebMD, HealthTap, eHealthForums, and iCliniq. © 2020 ACM.

关键词： Deep learning

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