Matches in SemOpenAlex for { <https://semopenalex.org/work/W4367172694> ?p ?o ?g. }
Showing items 1 to 58 of
58
with 100 items per page.
- W4367172694 abstract "The semiconductor manufacturing process is becoming more complex and time-consuming due to smaller design rules and denser patterns, which inevitably leads to an increase in the number and types of defects. In the past, considerable efforts have been made to classify defects, and this has been implemented at the equipment level. However, in order to enhance the efficiency and productivity of semiconductor process development by automatically classifying random, systematic, and parametric defects according to various process schemes and structures, there is a need for a deep learningbased automatic defect classification technique with a higher degree of freedom and utilization. In this study, we used not only scanning electron microscope images, which have been actively studied, but also optical inspection images at various scales. Deep learning algorithms were evaluated for various layers of memory devices to select the optimal algorithm for each layer, and an accuracy of 94% or more was achieved, even with a small sample size (under 1000), which is critical in the R&D stage. It is expected that this technique will be able to spread and be applied to more diverse layers in the future. By providing faster and more diverse classifications of defects in semiconductor manufacturing processes and ensuring higher consistency through continuous sample size expansion, it is anticipated that this technique will contribute to shortening the development period and improving yield." @default.
- W4367172694 created "2023-04-28" @default.
- W4367172694 creator A5018749748 @default.
- W4367172694 creator A5029788267 @default.
- W4367172694 creator A5050112486 @default.
- W4367172694 creator A5061130894 @default.
- W4367172694 creator A5067237923 @default.
- W4367172694 creator A5076288865 @default.
- W4367172694 creator A5077009957 @default.
- W4367172694 creator A5088010007 @default.
- W4367172694 date "2023-04-27" @default.
- W4367172694 modified "2023-09-29" @default.
- W4367172694 title "Deep learning-based automatic defect classification for semiconductor manufacturing" @default.
- W4367172694 doi "https://doi.org/10.1117/12.2658638" @default.
- W4367172694 hasPublicationYear "2023" @default.
- W4367172694 type Work @default.
- W4367172694 citedByCount "0" @default.
- W4367172694 crossrefType "proceedings-article" @default.
- W4367172694 hasAuthorship W4367172694A5018749748 @default.
- W4367172694 hasAuthorship W4367172694A5029788267 @default.
- W4367172694 hasAuthorship W4367172694A5050112486 @default.
- W4367172694 hasAuthorship W4367172694A5061130894 @default.
- W4367172694 hasAuthorship W4367172694A5067237923 @default.
- W4367172694 hasAuthorship W4367172694A5076288865 @default.
- W4367172694 hasAuthorship W4367172694A5077009957 @default.
- W4367172694 hasAuthorship W4367172694A5088010007 @default.
- W4367172694 hasConcept C108583219 @default.
- W4367172694 hasConcept C119599485 @default.
- W4367172694 hasConcept C119857082 @default.
- W4367172694 hasConcept C127413603 @default.
- W4367172694 hasConcept C154945302 @default.
- W4367172694 hasConcept C160671074 @default.
- W4367172694 hasConcept C41008148 @default.
- W4367172694 hasConcept C66018809 @default.
- W4367172694 hasConceptScore W4367172694C108583219 @default.
- W4367172694 hasConceptScore W4367172694C119599485 @default.
- W4367172694 hasConceptScore W4367172694C119857082 @default.
- W4367172694 hasConceptScore W4367172694C127413603 @default.
- W4367172694 hasConceptScore W4367172694C154945302 @default.
- W4367172694 hasConceptScore W4367172694C160671074 @default.
- W4367172694 hasConceptScore W4367172694C41008148 @default.
- W4367172694 hasConceptScore W4367172694C66018809 @default.
- W4367172694 hasLocation W43671726941 @default.
- W4367172694 hasOpenAccess W4367172694 @default.
- W4367172694 hasPrimaryLocation W43671726941 @default.
- W4367172694 hasRelatedWork W3014300295 @default.
- W4367172694 hasRelatedWork W3164822677 @default.
- W4367172694 hasRelatedWork W4223943233 @default.
- W4367172694 hasRelatedWork W4225161397 @default.
- W4367172694 hasRelatedWork W4309045103 @default.
- W4367172694 hasRelatedWork W4312200629 @default.
- W4367172694 hasRelatedWork W4360585206 @default.
- W4367172694 hasRelatedWork W4364306694 @default.
- W4367172694 hasRelatedWork W4380075502 @default.
- W4367172694 hasRelatedWork W4380086463 @default.
- W4367172694 isParatext "false" @default.
- W4367172694 isRetracted "false" @default.
- W4367172694 workType "article" @default.