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https://open.uns.ac.rs/handle/123456789/12864
Title: | A Hybrid Automatic Classification Model for Skin Tumour Images | Authors: | Simić S. Simić S. Banković Z. Ivkov Simić, Milana Villar J. Simić, Dragan |
Issue Date: | 1-Jan-2019 | Journal: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Abstract: | © 2019, Springer Nature Switzerland AG. In medical practice early accurate detection of all types of skin tumours is essential to guide appropriate management and improve patients’ survival. The most important is to differentiate between malignant skin tumours and benign lesions. The aim of this research is classification of skin tumours by analyzing medical skin tumour dermoscopy images. This paper is focused on a new strategy based on hybrid model which combines mathematics and artificial techniques to define strategy to automatic classification for skin tumour images. The proposed hybrid system is tested on well-known HAM10000 data set, and experimental results are compared with similar researches. | URI: | https://open.uns.ac.rs/handle/123456789/12864 | ISBN: | 9783030298586 | ISSN: | 3029743 | DOI: | 10.1007/978-3-030-29859-3_61 |
Appears in Collections: | FTN Publikacije/Publications |
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