… to classify observed objects into semantically meaningful categories. In this paper we focus
on vehicle classification … Again, there is a need to classify objects into subclasses, to support …

… If fine-grained classification of vehicle is applied in transportation and public security, we
can acquire more meta information like vehicle make, model, logo, production year, max speed …

… road vehicle classification system, which automatically determines both vehicle type (car,
van , HGV) and the vehicle … of the foreground blob corresponding to the segmented vehicle. …

… In order to capture rich and discriminative information of vehicles, we introduce sparse
Laplacian filter learning to obtain the filters of the network with large amounts of unlabeled data. …

… In this paper, we take all of these simple and rotated prototypes to represent a vehicle image
patch, … The concept of “integral image” is used to compute a rich set of Haar-like features. …

… Although the classification of vehicle types has been a subject … of a vehicle [6] or the
classification of vehicles into broad … Most vehicles have different appearances, with rich edge …

… Cars are now indispensable from our modern life as a vehicle for transportation. In many …
The enormous number of car designs and car model makes car a rich object class, which can …

… satisfy the on-board requirement to detect vehicles, pedestrians, or traffic signals. The images
obtained contain rich semantic information, but graphic computation consumes computer …

… vehicle. In this paper we present a stochastic multi-class vehicle classification system which
classifies a vehicle (… Grimson, “Edge-based rich representation for vehicle classification,” in …

… Currently, many object detection models are based on convolutional neural networks (CNNs)
due to their rich representation power [6]. The visual recognition performed by the CNN …