Endang Sugiharti, Riza Arifudin, Devi Ajeng Efrilianda, Arief Broto Susilo, Nugraha Dwi Putra
As the amount of data and information about cancer features has grown dramatically, a growing number of researchers have turned to Machine Learning technology and Deep Learning strategies. The growing interest in deep learning has made Convolutional Neural Network (CNN) the most used method for image analysis and classification. Mask Region-based Convolutional Neural Network (Mask R-CNN) is a new CNN method for object detection and segmentation. The objectives of this study are: (1) To reveal the stages of implementing of Mask R-CNN for the detection of skin cancer. (2) To obtain the level of accuracy of Mask R-CNN for detection of skin cancer. Methods include: (1) Data collection. (2) separating the dataset into training and validation. (3) Stages of Mask R-CNN. The results, (1) Obtained the implementation stage of Mask R-CNN for detection of skin cancer. (2) Accuracy results obtained by Mask R-CNN in detecting Skin Cancer. © 2023 Author(s).
Computer Science Department, Universitas Negeri Semarang, Semarang, Indonesia
