A Quantum-Classical Hybrid Method for Image Classification and Segmentation
Quantum Physics
2021-12-07 v2
Abstract
Enormous activity in the Quantum Computing area has resulted in considering them to solve different difficult problems, including those of applied nature, together with classical computers. An attempt is made in this work to nail down a pipeline consisting of both quantum and classical processing blocks for the task of image classification and segmentation in a systematic fashion. Its efficacy and utility are brought out by applying it to Surface Crack segmentation. Being a sophisticated software engineering task, the functionalities are orchestrated through our in-house Cognitive Model Management framework.
Cite
@article{arxiv.2109.14431,
title = {A Quantum-Classical Hybrid Method for Image Classification and Segmentation},
author = {Sayantan Pramanik and M Girish Chandra and C V Sridhar and Aniket Kulkarni and Prabin Sahoo and Vishwa Chethan D and Hrishikesh Sharma and Ashutosh Paliwal and Vidyut Navelkar and Sudhakara Poojary and Pranav Shah and Manoj Nambiar},
journal= {arXiv preprint arXiv:2109.14431},
year = {2021}
}
Comments
11 pages, 16 figures, (v2) References and typographical errors fixed