Automating microscopic image analysis post-photolithography with machine learning
Fulfagar, Hardik Sandeep
Loading…
Permalink
https://hdl.handle.net/2142/124402
Description
Title
Automating microscopic image analysis post-photolithography with machine learning
Author(s)
Fulfagar, Hardik Sandeep
Issue Date
2024-04-29
Director of Research (if dissertation) or Advisor (if thesis)
Nahrstedt, Klara
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Machine Learning
Computer Vision
Semiconductor Photolithography
Microscopic Image Analysis Automation
Dataset Creation
Image Classification
Semiconductor Defect Detection
Language
eng
Abstract
This thesis addresses the challenges in the manual analysis of semiconductor images by leveraging machine learning techniques to automate the process, with a focus on the photolithography stage. We compare various machine learning techniques for classifying images based on exposure and development levels, aimed at overcoming the limitations of human error in traditional analysis methods. In this thesis, we have created a dataset and used a comprehensive framework for the application of machine learning models. By shifting the focus from merely detecting surface defects to understanding the underlying causes during the photolithography process, this research aims to provide more targeted solutions for improving semiconductor manufacturing and understanding the errors. The findings of this thesis have the potential to enhance methodological precision and efficiency in semiconductor research, particularly beneficial in academic settings for instant analysis and feedback, thereby improving the learning experience for students studying this critical phase of semiconductor manufacturing.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
