  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
