Lentigo detection using a deep learning approach - Traitement et Compréhension d’Images Access content directly
Conference Papers Year : 2020

Lentigo detection using a deep learning approach


Reflectance confocal microscopy (RCM) allows fast data acquisition with a high resolution of the skin. In fact, RCM images are becoming more and more used for lentigo diagnosis. In this paper, we propose a new classification method to automate specific steps in lentigo diagnosis. Our method is based on a convolutional neural network (CNN) on InceptionV3 architecture combined with data augmentation and transfer learning. The experimental validation showed the efficiency of our model by reaching an accuracy of 98.14%.
Fichier principal
Vignette du fichier
zorgui_26415.pdf (966.31 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-02968415 , version 1 (15-10-2020)



Sana Zorgui, Siwar Chaabene, Hadj Batatia, Lotfi Chaari. Lentigo detection using a deep learning approach. International Conference On Smart Living and Public Health (ICOST 2020), Jun 2020, Hammamet, Tunisia. pp.1-5, ⟨10.1007/978-3-030-51517-1_8⟩. ⟨hal-02968415⟩
137 View
106 Download



Gmail Mastodon Facebook X LinkedIn More