DEVELOPMENT OF A MODEL OF OBJECT RECOGNITION IN IMAGES BASED ON THE «TRANSFER LEARNING» METHOD

Authors

  • Yaxshiboyev Rustam Erkinboy o'g'li TUIT named after Muhammad al-Khwarizmi

Keywords:

analysis, algorithm, detection, method, transfer learning

Abstract

This article is devoted to the study of “transfer learning” and the development of an object recognition model in images based on the “Transfer learning” method. Apartment creation software and Python packages, Yolov5 algorithm and roboflow.com used website data. In the process of work, a model was developed for recognizing objects in images based on the “Transfer learning” method, and the resulting model was tested

References

Постановление Президента Республики Узбекистан, от 17.02.2021 г. № ПП-4996. lex.uz/docs/5297051

Предварительная прогнозирование медицинских заболеваний с помощью нейронных сетей. Яхшибоева Д.Э. Material of International students conference.2021

Цифровые технологии в диагностике и лечении неврологических заболеваний. Н.В.Петухова, М.П.Фархадов, М.В.Замерград, С.П.Грачев. 2022.

Разработка и исследование алгоритмов сегментации и распознавания объектов на медицинских изображениях на основе шиарлет-преобразования и нейронных сетей. Хамад Ю.А. 2020.

Методы повышения эффективности нейросетевых рекомендательных систем в условиях ограниченных объемов выборок со сложными корреляционными связями (на примере диагностики и прогнозирования сердечно-сосудистых заболеваний человека). Черепанов Ф.М. 2019.

V-Net — Volumetric Convolution (Biomedical Image Segmentation).Sik-Ho Tsang. 2019.

Andersson J, Ahlström H, Kullberg J (September 2019). "Separation of water and fat signal in whole-body gradient echo scans using convolutional neural networks"

Long, J.; Shelhamer, E. & Darrell, T. (2014), Fully convolutional networks for semantic segmentation

M. B. Boltaevich, N. R. H. ogli, G. N. S. qizi and M. S. S. ogli, "Estimation affects of formats and resizing process to the accuracy of convolutional neural network," 2019 International Conference on Information Science and Communications Technologies (ICISCT), 2019, pp. 1-5, doi: 10.1109/ICISCT47635.2019.9011858.

Muminov, B., et al. "Localization and Classification of Myocardial Infarction Based on Artificial Neural Network,(2020) 2020 Information Communication Technologies Conference." (2020): 245-249.

R. Yakhshibaev, B. Turaev, K. Jamolov, N. Atadjanova, E. Kim and N. Sayfullaeva, "Development of a mathematical model for balancing the level and device for remote monitoring of groundwater parameters," 2021 International Conference on Information Science and Communications Technologies (ICISCT), 2021, pp. 1-4, doi: 10.1109/ICISCT52966.2021.9670022

Yaxshiboyev, Rustam, and Dilbar Yaxshiboyeva. "ANALYSIS OF ALGORITHMS FOR PREDICTION AND PRELIMINARY DIAGNOSTICS OF GASTROENTEROLOGICAL DISEASES." CENTRAL ASIAN JOURNAL OF EDUCATION AND COMPUTER SCIENCES (CAJECS) 1.2 (2022): 49-56.

Ermetov E. Y. Yaxshiboyev RE Gastroenterologik kasalliklarni KNN algoritmi asosida bashoratlovchi dastur //О ‘zbekiston Respublikasi intellektual mulk agentligi. Elektron hisoblash mashinalari uchun yaratilgan dasturning rasmiy ro’yxatdan o’tkazilganligi to’g’risidagi guvohnoma.№ DGU. – Т. 17014.

Ermetov E. Y. Yaxshiboyev RE Gastroenterologik kasalliklarni ANN algoritmi asosida bashoratlovchi dastur //О ‘zbekiston Respublikasi intellektual mulk agentligi. Elektron hisoblash mashinalari uchun yaratilgan dasturning rasmiy ro’yxatdan o’tkazilganligi to’g’risidagi guvohnoma.№ DGU. – Т. 17016.

Ermetov E. Y. Yaxshiboyev RE Gastroenterologik kasalliklarni SVM algoritmi asosida bashoratlovchi dastur //О ‘zbekiston Respublikasi intellektual mulk agentligi. Elektron hisoblash mashinalari uchun yaratilgan dasturning rasmiy ro’yxatdan o’tkazilganligi to’g’risidagi guvohnoma.№ DGU. – Т. 17015

Yaxshiboyev, R. E., et al. "FORECASTING GROUNDWATER EVAPORATION USING MULTIPLE LINEAR REGRESSION." Galaxy International Interdisciplinary Research Journal 9.12 (2021): 1101-1107.

Djumanov, Jamoljon, et al. "Mathematical model and software package for calculating the balance of information flow." 2021 International Conference on Information Science and Communications Technologies (ICISCT). IEEE, 2021

“Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython”, 2-nashr - Ues Makkinni (O’reilly, 2017).

“Understanding Machine Learning: From Theory to Algorithms” - Shai Shalev-Shvarts va Shai Ben-David (Cambridge University Press, 2014).

“Programming Computer Vision with Python” - Jan Erik Solem (Creative Commons, 2012).

“Обработка изображений с помощью OpenCV” – Gloria Bueno, Ismael Serrano Garsiya, Noeliya Vallez, Oskar Denis Suarez, Xesus Salido, Espinosa Aranda (DMK Press, 2016).

“Computer Vision and Machine Learning based Hand Gesture Recognition” – Paulo Trigeros, Fernando Ribeyro, Luis Paulo Reis (Scholaar Press, 2015).

“Система распознавания жестов из ограниченного набора” - Александр Носов (LAP Lambert Academic Publishing 2012).

Mo'minov B., Dauletov A. CLASSES OF ELECTRONIC DOCUMENT CIRCULATION SYSTEMS AND MATHEMATICAL MODELS OF PROCESSING //CENTRAL ASIAN JOURNAL OF EDUCATION AND COMPUTER SCIENCES (CAJECS). – 2022. – Т. 1. – №. 2. – С. 6-16.

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Published

2022-08-28

How to Cite

Yaxshiboyev, R. (2022). DEVELOPMENT OF A MODEL OF OBJECT RECOGNITION IN IMAGES BASED ON THE «TRANSFER LEARNING» METHOD. CENTRAL ASIAN JOURNAL OF EDUCATION AND COMPUTER SCIENCES (CAJECS), 1(4), 36–41. Retrieved from https://cajecs.com/index.php/cajecs/article/view/v1i45

Issue

Section

Technical sciences

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