The article presents the results of the development of an algorithm and a desktop application for recognizing Russian-language handwritten text in images using computer vision and deep learning technologies. Classical and modern recognition methods have been studied and an algorithm has been developed and implemented that ensures 71% recognition accuracy. The application allows the user to upload images receive digitized text and save the results in his personal account. The software implementation includes a training block for the model with an assessment of accuracy and completeness metrics. The application meets all the set requirements providing ease of use and functionality.

Keywords: deep learning, handwritten text, image, data, model training, computer vision, feature extraction, CTC, RNN, CNN, CRNN