1. A method for classifying a vehicle type, comprising: performing scale aware detection; performing detection assisted sampling for convolutional neural network (CNN) training; and performing deep CNN fine grained image classification to classify the vehicle type; wherein the scale aware detection is trained using a Regionlet detector, the Regionlet detector is a boosting classifier composed of weak classifiers: H ⁡ ( x ) = ∑ i = 1 T ⁢ h i ⁡ ( x ) , wherein T is the total number of training stages, h(x) is the weak classifier learned at stage t in training, x is the input image, wherein the weak classifier h(x) is written as a function of the spatial location of Regionlets in h, and a feature used for h: 
 h t ( x )= G ( p t , f t , x ), wherein p is a set of Regionlet locations, f is the feature extracted in the set of Regionlet locations.