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Population growth and the high concentration of vehicles on urban roads have negatively impacted urban mobility and the global environment since the primary transportation modes occupy a lot of space on the streets and are one of the main polluting gas emitters. In this context of inefficient urban mobility and unsustainability, the Intelligent Transportation Systems (ITS) aims to solve or minimize urban traffic issues. ITS are also widely used in applications focused on traffic safety, such as vehicle recognition related to a traffic or law violation. For this task, the fine-grained vehicle classification technique is mainly used by computer vision and deep learning advances. However, identifying vehicles by the model can be problematic because the same vehicle can be easily misclassified when observed from different perspectives, with different colours, or by similar models. Knowing these inherent issues from vehicle …