Abstract
Producing defect‐free products is one of the essential tasks of a manufacturing company. In this paper, the causes of dead pixels are analyzed and the coordinates of dead pixels are predicted using machine learning to solve problems of dead pixels. Unlike the existing method of analyzing defects using images, tabular data where each element contains significance were used, and detailed description of suggested models are depicted. Experiments ensured the consistency of the proposed method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
