Identifikasi Objek Cagar Budaya Candi Mahligai Berbasis Citra Digital Menggunakan Mask R-CNN - Regiolina Hayami; Elvina Rahmadani; Yoze Rizki (Jurnal CoSciTech (Computer Science and Information Technology), 2022)
Object detection is determining the existence of an object and its scope and location in an image. Excessive historical relics and it is generally difficult for humans to remember all the names. One of the fields of science that supports in facilitating human work is confidence score. The main problem in confidence score is how to recognize images and make use of the images they capture. The purpose of this research is to identify the image of Mahligai Temple. This research uses the Deep Learning Mask R-CNN algorithm as a detection of image objects that can recognize cultural heritage sites. The application is carried out on the image of Mahligai Temple. The results using Confussion Matrix and obtained an accuracy of 82.0%, precision 78.57% and recall 88.0%. Single Class identification done successfully at the threshold value 0.776 with error percentage of 18%.