A Study on Halftoning Improvement for Low-Resolution Digital Print Engines With Machine Learning Methods-Reference-Cited by-同舟云学术

A Study on Halftoning Improvement for Low-Resolution Digital Print Engines With Machine Learning Methods

Published:2022 Issue: Volume:10 Page:19780-19795
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Frank Tal¹^ORCID,Haik Oren²^ORCID,Gat Shani²,Mor Orel Bat²,Allebach Jan P.³,Yitzhaky Yitzhak¹^ORCID

Affiliation:

1. Department of Electro-Optics Engineering, School of Electrical and Computer Engineering, Ben Gurion University of the Negev, Be’er Sheva, Israel

2. Research and Development Department, HP Inc., Ness Ziona, Israel

3. School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09709797.pdf?arnumber=9709797

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