{"id":"https://openalex.org/W7131099115","doi":"https://doi.org/10.1109/iccvw69036.2025.00380","title":"Application of Semantic Segmentation on SEM Images of Rubber Composites and Verification of Correlation with Material Properties","display_name":"Application of Semantic Segmentation on SEM Images of Rubber Composites and Verification of Correlation with Material Properties","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W7131099115","doi":"https://doi.org/10.1109/iccvw69036.2025.00380"},"language":null,"primary_location":{"id":"doi:10.1109/iccvw69036.2025.00380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126590901","display_name":"Sho Sakamoto","orcid":null},"institutions":[{"id":"https://openalex.org/I120640012","display_name":"Sumitomo Rubber Industries (Japan)","ror":"https://ror.org/038rse530","country_code":"JP","type":"company","lineage":["https://openalex.org/I120640012"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sho Sakamoto","raw_affiliation_strings":["Sumitomo Rubber Industries,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sumitomo Rubber Industries,Japan","institution_ids":["https://openalex.org/I120640012"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045234881","display_name":"Wakana Miyoshi","orcid":null},"institutions":[{"id":"https://openalex.org/I120640012","display_name":"Sumitomo Rubber Industries (Japan)","ror":"https://ror.org/038rse530","country_code":"JP","type":"company","lineage":["https://openalex.org/I120640012"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Wakana Miyoshi","raw_affiliation_strings":["Sumitomo Rubber Industries,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sumitomo Rubber Industries,Japan","institution_ids":["https://openalex.org/I120640012"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020744499","display_name":"K Oishi","orcid":"https://orcid.org/0000-0001-5367-6619"},"institutions":[{"id":"https://openalex.org/I120640012","display_name":"Sumitomo Rubber Industries (Japan)","ror":"https://ror.org/038rse530","country_code":"JP","type":"company","lineage":["https://openalex.org/I120640012"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kentaro Oishi","raw_affiliation_strings":["Sumitomo Rubber Industries,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sumitomo Rubber Industries,Japan","institution_ids":["https://openalex.org/I120640012"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010272932","display_name":"Ryuta Asami","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryuta Asami","raw_affiliation_strings":["NEC,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC,India","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041807527","display_name":"Akira Kobayashi","orcid":"https://orcid.org/0000-0001-8190-6776"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Kobayashi","raw_affiliation_strings":["NEC,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC,India","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126595082","display_name":"Hiroki Iwana","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki Iwana","raw_affiliation_strings":["NEC,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC,India","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078596110","display_name":"Taichi Tokunaga","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taichi Tokunaga","raw_affiliation_strings":["NEC,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC,India","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062011531","display_name":"Yosuke Motohashi","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yosuke Motohashi","raw_affiliation_strings":["NEC,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC,India","institution_ids":["https://openalex.org/I118347220"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55520425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3643","last_page":"3651"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12039","display_name":"Electron and X-Ray Spectroscopy Techniques","score":0.11010000109672546,"subfield":{"id":"https://openalex.org/subfields/2508","display_name":"Surfaces, Coatings and Films"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12039","display_name":"Electron and X-Ray Spectroscopy Techniques","score":0.11010000109672546,"subfield":{"id":"https://openalex.org/subfields/2508","display_name":"Surfaces, Coatings and Films"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.08500000089406967,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11856","display_name":"Thermography and Photoacoustic Techniques","score":0.06270000338554382,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/natural-rubber","display_name":"Natural rubber","score":0.7439000010490417},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6254000067710876},{"id":"https://openalex.org/keywords/scanning-electron-microscope","display_name":"Scanning electron microscope","score":0.5367000102996826},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5353999733924866},{"id":"https://openalex.org/keywords/material-properties","display_name":"Material properties","score":0.4894999861717224},{"id":"https://openalex.org/keywords/digital-image-correlation","display_name":"Digital image correlation","score":0.445499986410141},{"id":"https://openalex.org/keywords/filler","display_name":"Filler (materials)","score":0.44020000100135803}],"concepts":[{"id":"https://openalex.org/C176933379","wikidata":"https://www.wikidata.org/wiki/Q131877","display_name":"Natural rubber","level":2,"score":0.7439000010490417},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.6265000104904175},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6254000067710876},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.618399977684021},{"id":"https://openalex.org/C26771246","wikidata":"https://www.wikidata.org/wiki/Q321095","display_name":"Scanning electron microscope","level":2,"score":0.5367000102996826},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5353999733924866},{"id":"https://openalex.org/C31555180","wikidata":"https://www.wikidata.org/wiki/Q3523867","display_name":"Material properties","level":2,"score":0.4894999861717224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47380000352859497},{"id":"https://openalex.org/C115635565","wikidata":"https://www.wikidata.org/wiki/Q860900","display_name":"Digital image correlation","level":2,"score":0.445499986410141},{"id":"https://openalex.org/C2778223994","wikidata":"https://www.wikidata.org/wiki/Q905592","display_name":"Filler (materials)","level":2,"score":0.44020000100135803},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39149999618530273},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38580000400543213},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38499999046325684},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C521977710","wikidata":"https://www.wikidata.org/wiki/Q81163","display_name":"Polymer","level":2,"score":0.3425999879837036},{"id":"https://openalex.org/C2778517922","wikidata":"https://www.wikidata.org/wiki/Q7140482","display_name":"Particle (ecology)","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.31220000982284546},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C519885992","wikidata":"https://www.wikidata.org/wiki/Q161","display_name":"Fiber","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C187530423","wikidata":"https://www.wikidata.org/wiki/Q7140503","display_name":"Particle size","level":2,"score":0.25839999318122864}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccvw69036.2025.00380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2424211690","https://openalex.org/W2963904459","https://openalex.org/W4200632538","https://openalex.org/W4214893857","https://openalex.org/W4283311093","https://openalex.org/W4300818599","https://openalex.org/W4390189988","https://openalex.org/W4402916256","https://openalex.org/W4408017302"],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1,145],"aims":[2],"to":[3,7],"apply":[4],"semantic":[5],"segmentation":[6,64,107],"scanning":[8],"electron":[9],"microscopy":[10],"(SEM)":[11],"images":[12,81],"of":[13,34,38,65,132,143,157],"rubber":[14,35,133,158],"composites":[15,36,159],"and":[16,18,27,41,47,67,87,121,135,152,160,173],"quantitatively":[17,92],"comprehensively":[19],"evaluate":[20],"the":[21,57,88,95,103,129],"correlation":[22,110],"between":[23,112],"extracted":[24],"image":[25,32,155],"features":[26,114],"physical":[28,122],"properties.":[29],"Traditionally,":[30],"SEM":[31,78,154],"analysis":[33,111,156],"composed":[37],"multiple":[39],"fillers":[40],"polymers":[42],"has":[43],"relied":[44],"on":[45,56],"visual":[46],"qualitative":[48],"assessments.":[49],"However,":[50],"by":[51],"employing":[52],"a":[53,147,163],"model":[54,73,104],"based":[55],"U-Net":[58],"architecture,":[59],"we":[60],"achieved":[61],"high-precision":[62],"pixel-level":[63],"filler":[66],"polymer":[68],"regions.":[69],"A":[70],"multi-class":[71],"classification":[72],"was":[74,91],"constructed":[75],"targeting":[76],"quaternary":[77],"images.":[79],"Expert-annotated":[80],"were":[82],"used":[83],"as":[84,162],"training":[85],"data,":[86],"model's":[89],"performance":[90],"evaluated":[93],"using":[94],"F1":[96],"score.":[97],"The":[98,141],"evaluation":[99],"results":[100],"demonstrated":[101],"that":[102,125],"attained":[105],"sufficient":[106],"accuracy.":[108],"Furthermore,":[109],"fundamental":[113],"(e.g.,":[115],"particle":[116],"size,":[117],"perimeter,":[118],"inter-aggregate":[119],"distance)":[120],"properties":[123,131],"revealed":[124],"formulation":[126],"conditions":[127],"influence":[128,137],"mechanical":[130],"composites,":[134],"this":[136,144],"can":[138],"be":[139],"visualized.":[140],"findings":[142],"propose":[146],"novel":[148],"approach":[149],"for":[150,166],"quantitative":[151],"automated":[153],"serve":[161],"powerful":[164],"tool":[165],"understanding":[167],"structure\u2013property":[168],"relationships":[169],"in":[170],"material":[171],"design":[172],"defect":[174],"analysis.":[175]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-24T00:00:00"}