Brahmi Script Classification using VGG16 Architecture Convolutional Neural Network

Many Indonesians have difficulty reading and learning the Brahmi script. Solving these problems can be done by developing software. Previous research has classified script but not had an output that matches letter. Therefore, letter classification is carried out as part of process recognizing This study uses Convolutional Neural Network (CNN) method with VGG16 architecture for classifying writing. Training results from various amounts image data. Smooth model. The requested data a 224x224 binary image. highest quality, accuracy 96%, recall 98% precision 98%.