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http://hdl.handle.net/20.500.12188/26055| Title: | Classification of Digital Images using topological signatures – A Case Study | Authors: | Petar Sekuloski Dimitrievska Ristovska, Vesna |
Keywords: | TOPOLOGICAL DATA ANALYSIS, PERSISTENT HOMOLOGY, MACHINE LEARNING, COMPUTATIONAL TOPOLOGY | Issue Date: | Dec-2022 | Publisher: | Scientific Technical Union of Mechanical Engineering" Industry 4.0" | Source: | https://stumejournals.com/journals/mm/2022/4/106 | Journal: | International Scientific Journal "Mathematical Modeling" | Series/Report no.: | Volume 6;Iss. 4 | Conference: | International Scientific Conference "Mathematical Modeling", Borovets 2022 | Abstract: | Topological Data Analysis (TDA) is relatively new filed of Applied Mathematics that emerged rapidly last years. The main tool of Topological Data Analysis is Persistent Homology. Persistent Homology provides some topological characteristics of the datasets. In this paper we will discuss classification of digital images using their topological signatures computed with Persistent Homology. We will experiment on the Fashion-MNIST dataset. Using Topological Data Analysis, the classification was improved. | URI: | http://hdl.handle.net/20.500.12188/26055 | ISSN: | 2535-0986 |
| Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| mm-2022-4-106 Classification of Digital Images using topological signatures – A Case Study.pdf | 1.23 MB | Adobe PDF | View/Open |
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