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Procedia Computer Science
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
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ZENODO
Article . 2023
License: CC BY
Data sources: ZENODO
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Conference object . 2025
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A Review Study on ML-based Methods for Defect-Pattern Recognition in Wafer Maps

Authors: Theodosis Theodosiou; Aikaterini Rapti; Konstantinos Papageorgiou; Theodoros Tziolas; Elpiniki Papageorgiou; Nikolaos Dimitriou; George Margetis; +1 Authors

A Review Study on ML-based Methods for Defect-Pattern Recognition in Wafer Maps

Abstract

Abstract The identification of defects plays a key role in the semiconductor industry as it can reduce production risks, minimize the effects of unexpected downtimes and optimize the production process. A literature review protocol is implemented and latest advances are reported in defect detection considering wafer maps towards quality control. In particular, the most recent works are outlined to demonstrate the use of AI-technologies in wafer maps defect detection. The popularity of these technologies is then presented in the form of visualizing graphs. This enables the identification of the most popular and most prominent ML-methods that can be exploited for the purposes of Industry 4.0.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    15
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Top 10%
Top 10%
gold