PROJECT TITLE :

Vehicle Color Recognition With Spatial Pyramid Deep Learning

ABSTRACT:

Color, as a notable and stable attribute of vehicles, will serve as a useful and reliable cue in an exceedingly variety of applications in intelligent transportation systems. So, vehicle color recognition in natural scenes has become an important research topic in this area. In this paper, we have a tendency to propose a deep-learning-based mostly algorithm for automatic vehicle color recognition. Totally different from standard strategies, which sometimes adopt manually designed options, the proposed algorithm is able to adaptively learn illustration that is a lot of effective for the task of car color recognition, that results in higher recognition accuracy and avoids preprocessing. Moreover, we have a tendency to combine the widely used spatial pyramid strategy with the first convolutional neural network design, that additional boosts the recognition accuracy. To the most effective of our information, this can be the first work that employs deep learning in the context of vehicle color recognition. The experiments demonstrate that the proposed approach achieves superior performance over conventional strategies.