Pattern recognition with edge correction for design based metrology

A method for edge correction in pattern recognition includes generating a pattern recognition output for a pattern recognition process, including receiving, in the processor, a design layout, receiving a sample plan based on the design layout, receiving a first user-generated edge input, generating...

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Bibliographische Detailangaben
Hauptverfasser:	FISCHER DANIEL S, SHAO DONGBING, BAILEY TODD C
Format:	Patent
Sprache:	eng
Schlagworte:	APPARATUS SPECIALLY ADAPTED THEREFOR CALCULATING CINEMATOGRAPHY CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION ORPROCESSING OF GOODS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING ELECTROGRAPHY GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS HOLOGRAPHY MATERIALS THEREFOR ORIGINALS THEREFOR PHOTOGRAPHY PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES,e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTORDEVICES PHYSICS TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINSTCLIMATE CHANGE
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Beschreibung
Zusammenfassung:	A method for edge correction in pattern recognition includes generating a pattern recognition output for a pattern recognition process, including receiving, in the processor, a design layout, receiving a sample plan based on the design layout, receiving a first user-generated edge input, generating a pattern recognition recipe output from the design layout, the sample plan and the user-generated edge input, wherein the pattern recognition recipe output is configured to drive the pattern recognition process, generating a measurement model from the pattern recognition process, generating a measurement model pattern recognition output for an measurement model pattern recognition process, including receiving a second user-generated input and generating a measurement model pattern recognition recipe output from the measurement model and the second user-generated edge input, wherein the measurement model pattern recognition recipe output configured to drive the measurement model pattern recognition process.