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Machine Learning in Semiconductor Failure Analysis: Techniques and Case Studies

Year: 2024

Type: conference-paper

Source: Proceedings - International Symposium for Testing and Failure Analysis

DOI: 10.31399/asm.cp.istfa2024tpv1

Authors: Michael Kögel, Sebastian Brand, Frank Altmann

Institution: Fraunhofer Institute for Microstructure of Materials and Systems

Language: English

Topic: Integrated Circuits and Semiconductor Failure Analysis

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W4403684837

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