Optimasi Mendeteksi Klasifikasi Citra Digital Logo Mobil Indonesia Dengan Metode Single Shot Multibox Detector

- The car logo is one of the features that can identify a vehicle. However, many of the intelligent transportation systems are currently under development and do not yet use a car vehicle recognition system as part of a vehicle identification tool. The previous methods, namely the Local Binary Pattern and Random Forest Methods, had low recognition rates for most small vehicle logos and poor performance under complex environments. The aim of this research is to introduce a unique car logo and to improve detection of car logos in Indonesia. The logo that was later discovered was used to find the car brand in no time. In this study we use the Single Shot Multibox Detector method which is known to detect objects running on the Jupyter Notebook Application. The data used for this research is of a public nature obtained from the Kaggle website dataset source which contains a number of varying images. There are 7 classes of car brands, namely Volkswagen, Hyundai, Lexus, Mercedes, Peugeot, Renault, and Tesla. Data testing in this study obtained 1,240 images for training data and 270 images in the test data category that had been tested and resulted in an evaluation value with the best accuracy value of 98.89% and a loss value of 0.025%.