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A Hybrid Automatic Classification Model for Skin Tumour Images

  • Svetlana Simić [1] ; Simić, Svetislav D. [1] ; Zorana Banković [3] ; Milana Ivkov-Simić [1] ; Villar, José R. [2] Árbol académico ; Dragan Simić [1] Árbol académico
    1. [1] University of Novi Sad

      University of Novi Sad

      RS.VO.6.3194359, Serbia

    2. [2] Universidad de Oviedo

      Universidad de Oviedo

      Oviedo, España

    3. [3] Frontiers Media SA, Paseo de Castellana 77 (Madrid)
  • Localización: Hybrid Artificial Intelligent Systems. 14th International Conference, HAIS 2019: León, Spain, September 4–6, 2019. Proceedings / coord. por Hilde Pérez García Árbol académico, Lidia Sánchez González Árbol académico, Manuel Castejón Limas Árbol académico, Héctor Quintián Pardo Árbol académico, Emilio Santiago Corchado Rodríguez Árbol académico, 2019, ISBN 978-3-030-29858-6, págs. 722-733
  • Idioma: inglés
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  • Resumen
    • 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.


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