Car Type Recognition with Deep Neural Networks
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | 2016 IEEE Intelligent Vehicles Symposium, IV 2016 |
| Publisher | IEEE |
| Pages | 1115-1120 |
| ISBN (Print) | 9781509018215 |
| DOIs | |
| Publication status | Published - Jun 2016 |
| Publication type | A4 Article in a conference publication |
| Event | IEEE Intelligent Vehicles Symposium - Gothenburg, Sweden Duration: 19 Jun 2016 → 22 Jun 2016 http://iv2016.org/ |
Conference
| Conference | IEEE Intelligent Vehicles Symposium |
|---|---|
| Country | Sweden |
| City | Gothenburg |
| Period | 19/06/16 → 22/06/16 |
| Internet address |
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.