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Lentigo detection using a deep learning approach

Abstract : 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%.
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Submitted on : Thursday, October 15, 2020 - 4:48:39 PM
Last modification on : Friday, August 5, 2022 - 2:56:21 PM


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Sana Zorgui, Siwar Chaabene, Hadj Batatia, Lotfi Chaâri. 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⟩



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