Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/26053
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Petar Sekuloski | en_US |
dc.contributor.author | Dimitrievska Ristovska, Vesna | en_US |
dc.contributor.author | Vassil Grozdanov | en_US |
dc.date.accessioned | 2023-03-09T08:07:02Z | - |
dc.date.available | 2023-03-09T08:07:02Z | - |
dc.date.issued | 2022-12 | - |
dc.identifier.citation | https://www.ijsr.net/get_abstract.php?paper_id=SR221209034533 | en_US |
dc.identifier.issn | 2319-7064 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/26053 | - |
dc.description.abstract | Topological Data Analysis (TDA) is relatively new field of Applied Mathematics that emerged rapidly last years. The main tool of Topological Data Analysis is Persistent Homology. Persistent Homology tracks the topological features of datasets. In this paper we will introduce a novel model for image classification based on Persistent Homology. In the experimental part we the introduced new novel on real medical dataset. Using this model, the classification was improved. | en_US |
dc.description.sponsorship | Faculty of Computer Science and Engineering, at the Ss. Cyril and Methodius University in Skopje | en_US |
dc.language.iso | en | en_US |
dc.publisher | International Journal of Science and Research (IJSR) | en_US |
dc.relation.ispartof | International Journal of Science and Research (IJSR) | en_US |
dc.relation.ispartofseries | Volume 11;Iss.12 | - |
dc.subject | Topological Data Analysis, Persistent Homology, Machine Learning, Computational Topology, Image Classification | en_US |
dc.title | A novel model for image classification based on Persistent Homology | en_US |
dc.type | Journal Article | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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IJSR PS VDR 2022 SR221209034533.pdf | 472.82 kB | Adobe PDF | View/Open |
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