Computer

Browse

Now showing 1 - 1 of 1

Melanoma identification using convolutional neural networks
(2018) Louifi, Akram; Soulami, Ameur; CHERIFI, Dalila (Supervisor)
Melanoma is an extremely dangerous type of skin cancer causing fatal incidences, it’s also an increasing form of cancer around the world. Since the odds of recovering for the earlydiagnosed cases is very high, early detection of melanoma is vital. Computer assisted diagnosis have been used alongside traditional techniques so as to improve the reliability of detecting melanoma. In this project, a convolutional Neural network model designed from scratch as well as Transfer Learning using the pretrained model Inception v3 are used in order to develop a reliable tool able to detect melanoma that can used by clinicians and individual users. The results using Inception v3 model for dermoscopical images achieved the best results compared to our model. The results are compared to those of clinicians, which shows that the algorithms can be used reliably for the detection of melanoma.