Improving machine vision crack die detection with multi-kernel learning SVM

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Improving machine vision crack die detection with multi-kernel learning SVM

With the rising need to produce semiconductor parts with zero defects to support the growth of the automotive industry, where safety must be assured, it is vital to perform visual inspection throughout the assembly process to isolate and detect defects. Visual inspections performed by a human have t...

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Bibliographic Details
Main Author:	Abdullah, Mohd Khairi John
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2024
Subjects:	machine vision inspection semiconductor die crack detection machine learning Support Vector Machine (SVM)
Online Access:	https://eprints.nottingham.ac.uk/76585/

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