Abstract
In this paper, we focus on simple data-driven approach to solve deep
learning based on implementing the Mask R-CNN module by analyzing deeper
manipulation of datasets. We firstly approach to affine transformation
and projective representation to data augmentation analysis in order to
increasing large-scale data manually based on the state-of-the-art in
views of computer vision. Then we evaluate our method concretely by
connection our datasets by visualization data and completely in testing
to many methods to understand intelligent data analysis in object
detection and segmentation by using more than 5000 image according to
many similar objects. As far as, it illustrated efficiency of small
applications such as food recognition, grasp and manipulation in
robotics