  The paper presents a novel concept for collaborative descriptors between
deeply learned and hand-crafted features. To achieve this concept, we apply
convolutional maps for pre-processing, namely the convovlutional maps are used
as input of hand-crafted features. We recorded an increase in the performance
rate of +17.06 % (multi-class object recognition) and +24.71 % (car detection)
from grayscale input to convolutional maps. Although the framework is
straight-forward, the concept should be inherited for an improved
representation.
