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Title: Object Detection using YOLOv3
Author(s): Jamal Agha, Sana
Referee(s): Prof. Dr. Schenke, Michael
Prof. Dr. Hartmann, Karsten
Granting Institution: Hochschule Merseburg
Issue Date: 2021-11-04
Type: Bachelor thesis
Language: English
Publisher: Hochschulbibliothek, Hochschule Merseburg
URN: urn:nbn:de:gbv:542-1981185920-820219
Subjects: methods for object recognition
artificial neural networks
Transfer learning
Abstract: The aim of this work is to provide an overview of artificial neural networks and methods for object recognition within an image. Many methods will be thoroughly explained to gain perspective about the best approach to implement the image object detection system. Transfer learning should be used to keep track of the number of images required to train a small network. The results obtained can thus be compared and discussed.
Open Access: Open access publication
License: (CC BY 4.0) Creative Commons Attribution 4.0(CC BY 4.0) Creative Commons Attribution 4.0
Appears in Collections:Ingenieur- und Naturwissenschaften

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