Dataset of vehicle images for Indonesia toll road tariff classification

Ananto Tri Sasongko, Grafika Jati, Mohamad Ivan Fanany, Wisnu Jatmiko

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Vehicle classifications with different methods have been applied for many purposes. The data provided in this article is useful for classifying vehicle purposes following the Indonesia toll road tariffs. Indonesia toll road tariff regulations divide vehicles into five groups as follows, group-1, group-2, group-3, group-4, and group-5, respectively. Group-1 is a class of non-truck vehicles, while group-2 to group-5 are classes of truck vehicles. The non-truck class consists of the sedan, pick-up, minibus, bus, MPV, and SUV. Truck classes are grouped based on the number of truck's axles. Group-2 is a class of trucks with two axles, a group-3 truck with three axles, a group-4 truck with four axles, and a group-5 truck with five axles or more. The dataset is categorized into five classes accordingly, which are group-1, group-2, group-3, group-4, and group-5 images. The data made available in this article observes images of vehicles obtained using a smartphone camera. The vehicle images dataset incorporated with deep learning, transfer learning, fine-tuning, and the Residual Neural Network (ResNet) model can yield exceptional results in the classification of vehicles by the number of axles.

Original languageEnglish
Article number106061
JournalData in Brief
Volume32
DOIs
Publication statusPublished - Oct 2020

Keywords

  • Classification
  • Dataset
  • Deep learning
  • Fine-tuning
  • Transfer learning
  • Vehicle image

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