View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network
February 06, 2017 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Afshin Dehghan, Syed Zain Masood, Guang Shu, Enrique. G. Ortiz
arXiv ID
1702.01721
Category
cs.CV: Computer Vision
Cross-listed
cs.AI
Citations
54
Venue
arXiv.org
Last Checked
5 months ago
Abstract
This paper describes the details of Sighthound's fully automated vehicle make, model and color recognition system. The backbone of our system is a deep convolutional neural network that is not only computationally inexpensive, but also provides state-of-the-art results on several competitive benchmarks. Additionally, our deep network is trained on a large dataset of several million images which are labeled through a semi-automated process. Finally we test our system on several public datasets as well as our own internal test dataset. Our results show that we outperform other methods on all benchmarks by significant margins. Our model is available to developers through the Sighthound Cloud API at https://www.sighthound.com/products/cloud
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