Pendeteksian Jumlah Bangunan Berbasis Citra Menggunakan Metode Deep Learning - Bagaskara, Radhinka; Rizkita, Alya Khairunnisa; Fernandes, Rivaldo; Yulita, Winda (STIKOM Tunas Bangsa Pematangsiantar, 2022)
Counting residential houses is one of the problems faced when determining population density level in Indonesia, therefore it’s required to find a method that’s able to solve said problem. Deep learning method is capable of creating a prediction model for detecting the number of buildings from an image. The deep learning prediction model is created with MobileNetv2 application. The prediction model is trained by using a dataset from Kaggle. The prediction model is tested using satellite photos taken from Way Kandis-Sukarame, Bandar Lampung. The result is a deep learning prediction model with accuracy of 91.30% for SenseFly and 10.34% for Way Kandis dataset. The research can be further improved by using a better training and testing dataset