چکیده مقاله
Melanoma skin cancer is one of the most lethal forms of cancer Deep learning has shown promising results in predicting melanoma skin cancer This paper proposes a novel method for skin cancer prediction using two modified networks: DenseNet121 and VGG19 In the proposed method, image augmentation is initially performed to increase the diversity of the training data, thereby enhancing the model’s generalization capability Subsequently, the capabilities of the two networks are enhanced by adding two dense layers with 2560 and 1200 neurons, respectively The proposed method is applied to the three class ISIC 2017 dataset, taking into account metrics such as Accuracy, Precision, Recall, and F measures The results of the proposed method have shown improvement over many other published works, demonstrating its effectiveness in skin cancer prediction
کلیدواژهها
نویسندگان
Sekineh Asadi Amiri
Department of Computer Engineering, University of Mazandaran, Babolsar, Iran
Amirhossein Zare Kordkheili
Department of Computer Engineering, University of Mazandaran, Babolsar, Iran
شیوه ارجاع
Asadi Amiri, Sekineh and Zare Kordkheili, Amirhossein,1403,Melanoma Skin Cancer Prediction Using VGG19 and DenseNet121,1st International Congress on Cancer Prevention,Zanjan
ارائهشده در
مجموعه مقالات اولین کنگره بین المللی پیشگیری از سرطان28 شهریور 1403 · زنجان