# Car Type Recognition with Deep Neural Networks

arXiv: https://arxiv.org/abs/1602.07125 · HTML: https://mlsanity.com/paper/1602.07125/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Feb 2016.

## Built on by (most cited first, 4 of 4)

- [Densely-Populated Traffic Detection using YOLOv5 and Non-Maximum Suppression Ensembling](https://mlsanity.com/paper/2108.12118/) (2021)
- [DELAUNAY: a dataset of abstract art for psychophysical and machine learning research](https://mlsanity.com/paper/2201.12123/) (2022)
- [Vehicle and License Plate Recognition with Novel Dataset for Toll Collection](https://mlsanity.com/paper/2202.05631/) (2022)
- [Explainable Part-Based Vehicle Classifier with Spatial Awareness](https://mlsanity.com/paper/2605.07831/) (2026)

## Abstract (arXiv)

In this paper we study automatic recognition of cars of four types: Bus, Truck, Van and Small car. For this problem we consider two data driven frameworks: a deep neural network and a support vector machine using SIFT features. The accuracy of the methods is validated with a database of over 6500 images, and the resulting prediction accuracy is over 97 %. This clearly exceeds the accuracies of earlier studies that use manually engineered feature extraction pipelines.