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Detection of Object Numbers Using Deep Learning Methods

Student: Kalashnikova Anastasiya

Supervisor: Elena Kantonistova

Faculty: Faculty of Computer Science

Educational Programme: Machine Learning and Data-Intensive Systems (Master)

Final Grade: 10

Year of Graduation: 2024

This work contains 35 pages, 23 figures, 5 tables, and 14 sources used. The graduation project is dedicated to the topic of detecting vehicle registration numbers in images. It includes several important steps: working with data, conducting experiments to select a relevant detector, and developing a service for the convenience of using the selected model. The paper investigated the theoretical foundations of some models that are used in the tasks of locating objects in the picture, then these detectors were applied in practice to the assembled dataset with vehicle numbers. The result of the thesis was a distributed service with an expanded model, which surpassed the rest in the course of experiments. Further prospects for the development of the project: increasing the number of classes of detectable objects; solving problems that are based on detection, such as recognition; working with the speed of obtaining detections; equipping the service with additional technical components; deploying the service on several nodes.

Full text (added June 3, 2024)

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