Object detection in mobile robotics

Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/17410

Title:	Object detection in mobile robotics
Authors:	Yakovyn, Valentyna Kriukov, Taras
Keywords:	computer vision object detection image classification machine learning mobile robotics software tools
Issue Date:	29-Nov-2022
Publisher:	Vasyl Stefanyk Precarpathian National University
Citation:	V. Yakovyn and T. Kriukov, "Software architecture design of software developed in student engineering teams," 2022 International Conference on Innovative Solutions in Software Engineering (ICISSE), Vasyl Stefanyk Precarpathian National University, Ivano-Frankivsk, Ukraine, Nov. 29-30, 2022, pp. 310-312, doi: 10.5281/zenodo.8418713
Abstract:	This paper presents an improved object detection method based on a combination of one-stage object detector followed by an additional classification stage. The article reports an increase in the IoU metric by 8%, classification accuracy by 7%, and f1-score by 5%.The research was conducted using computational experiments and modeling techniques. The results were discussed and interpreted.
URI:	https://zenodo.org/record/8418713 http://hdl.handle.net/123456789/17410
ISBN:	978-966-640-534-3
Appears in Collections:	Наукові роботи студентів, магістрантів, аспірантів (ФМІ)

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