Perbandingan Akurasi EfficientNetV2 dan MobileNetV2 pada Klasifikasi Makanan Tradisional Indonesia

Abstract

Machine learning is a rapidly evolving technology that has led to numerous advancements, especially in the field of computer vision. Within this domain, many models have been introduced, including EfficientNetV2 and MobileNetV2. Given the wide range of model choices, it is essential to compare the accuracy of each model. This involves data collection, resizing and sorting data, visualizing data, and finally tuning and training processes. In this study, it was found that the accuracy of EfficientNetV2 is 31%, while MobileNetV2 achieves an accuracy of 99%.