完整後設資料紀錄
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dc.contributor.authorTseng, Sean Shang-Enen_US
dc.contributor.authorChang, Wei-Chunen_US
dc.contributor.authorJiang, Iris Hui-Ruen_US
dc.contributor.authorZhu, Junen_US
dc.contributor.authorShiely, James P.en_US
dc.date.accessioned2020-05-05T00:02:01Z-
dc.date.available2020-05-05T00:02:01Z-
dc.date.issued2019-01-01en_US
dc.identifier.isbn978-1-5106-2569-3; 978-1-5106-2570-9en_US
dc.identifier.issn0277-786Xen_US
dc.identifier.urihttp://dx.doi.org/10.1117/12.2514818en_US
dc.identifier.urihttp://hdl.handle.net/11536/154071-
dc.description.abstractLayout features become highly susceptible to lithography process fluctuations due to the widening subwavelength lithography gap. Problematic layout patterns incur poor printability even if they pass design rule checking. These hotspots should be detected and removed at early design phases to improve manufacturability. While existing studies mainly focus on hotspot detection and pattern classification, hotspot pattern library generation is rarely addressed in literature but crucial to the effectiveness and efficiency of hotspot detection. For an advanced process, in addition to yield-limiting patterns inherent from old processes and computation intensive lithography simulation, defect silicon images (SEM images) inspected from test wafers provide more realistic process-dependent hotspots. For facilitating hotspot pattern library generation, we raise a pattern matching problem of searching design layout patterns that may induce problematic SEM images. The key challenge is the various shape distortions between an SEM image and corresponding design layouts. Directly matching either feature points or shapes of both is thus not applicable. We observe that even with shape distortions, matched design layouts and the SEM image have similar density distribution. Therefore, in this paper, we propose an efficient multilevel pixilation framework to seek layout clips with similar density distribution from coarse- to fine-granularities to an SEM image. The proposed framework possesses high parallelism. Our results show that the proposed method can effectively and efficiently identify matched layout pattern candidates.en_US
dc.language.isoen_USen_US
dc.subjectPattern matchingen_US
dc.subjecthotspot pattern libraryen_US
dc.subjecttemplate matchingen_US
dc.subjectmultilevel frameworken_US
dc.subjectpixelationen_US
dc.subjectSEM imagesen_US
dc.titleEfficient Search of Layout Hotspot Patterns for Matching SEM Images using Multilevel Pixelationen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1117/12.2514818en_US
dc.identifier.journalOPTICAL MICROLITHOGRAPHY XXXIIen_US
dc.citation.volume10961en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000526688400007en_US
dc.citation.woscount0en_US
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