Model Klasifikasi Penyakit Paru Melalui Citra Rontgen Dada Dengan Metode Convolutional Neural Network

Abstract

Convolutional Neural Network is a type of deep learning that is used for image detection or image classification. The images used can be obtained from data banks such as http://www.kaggle.com, the image usually has a different image format, different width and height sizes also in some images contain noise. Segmentation is used to separate the image that becomes information from the noise contained therein. The types of segmentation used are active contour compared to not using segmentation at all. The Convolutional Neural Network architecture was also changed to obtain a better level of accuracy, and to take advantage of the existing CNN architectures such as Alexnet and GoogleNet. From the research conducted, the best accuracy results were obtained from the RGB Image model combined with the GoogleNet model, namely 97.29%. Keywords:Convolutional Neural Network;Active Contour;accuracy;