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arXiv:1602.07125cs.CV

Car Type Recognition with Deep Neural Networks

Heikki Huttunen, Fatemeh Shokrollahi Yancheshmeh, Ke Chen

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Abstract

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.

arXiv comments
To appear in proceedings of IEEE Intelligent Vehicles Symposium 2016
Journal reference
In proceedings of IEEE Intelligent Vehicles Symposium 2016
DOI
doi:10.1109/IVS.2016.7535529
Subjects
cs.CVComputer Vision and Pattern Recognition

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Discussed in comments1 thread

  1. Implementation and Optimization of a DNN for Vehicle Classification [pdf] 1 comment

    • Based on the thesis [1] of one of the authors and the dataset [2] it links to, I believe it's {bus,truck,van,car} classification on a dataset of only vehicles. [1]: Dataflow-Based Implementation of Deep Learning Application…

      lovelearningView on HNParent context

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