{"id":"https://openalex.org/W4408862717","doi":"https://doi.org/10.1109/icce63647.2025.10930130","title":"DA-SAM: A Defect-Aware Segmentation Model for Industrial Product Inspection","display_name":"DA-SAM: A Defect-Aware Segmentation Model for Industrial Product Inspection","publication_year":2025,"publication_date":"2025-01-11","ids":{"openalex":"https://openalex.org/W4408862717","doi":"https://doi.org/10.1109/icce63647.2025.10930130"},"language":"en","primary_location":{"id":"doi:10.1109/icce63647.2025.10930130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce63647.2025.10930130","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Consumer Electronics (ICCE)","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/A5110493080","display_name":"Ju-Hui Hsu","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jen-Chueh Hsu","raw_affiliation_strings":["National Central University,Dept. of Computer Science and Information Engineering,Taoyuan,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Central University,Dept. of Computer Science and Information Engineering,Taoyuan,Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046617410","display_name":"Po-Chyi Su","orcid":"https://orcid.org/0000-0002-7457-8409"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Po-Chyi Su","raw_affiliation_strings":["National Central University,Dept. of Computer Science and Information Engineering,Taoyuan,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Central University,Dept. of Computer Science and Information Engineering,Taoyuan,Taiwan","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102105977","display_name":"Ching\u2010Wei Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ching-Wei Huang","raw_affiliation_strings":["Spingence, Inc.,AI laboratory,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Spingence, Inc.,AI laboratory,Taipei,Taiwan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109258456","display_name":"Yi-An Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi-An Lin","raw_affiliation_strings":["Spingence, Inc.,AI laboratory,Taipei,Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Spingence, Inc.,AI laboratory,Taipei,Taiwan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9045,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.73957401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11159","display_name":"Manufacturing Process and Optimization","score":0.9391000270843506,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9271000027656555,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6486297845840454},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.52006596326828},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.518703281879425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3951934576034546},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38003966212272644},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07155850529670715}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6486297845840454},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.52006596326828},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.518703281879425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3951934576034546},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38003966212272644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07155850529670715},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce63647.2025.10930130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce63647.2025.10930130","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2948982773","https://openalex.org/W2996290406","https://openalex.org/W3153381206","https://openalex.org/W3198377975","https://openalex.org/W3209793239","https://openalex.org/W4386065385","https://openalex.org/W4390874575","https://openalex.org/W6759579507","https://openalex.org/W6791353385","https://openalex.org/W6796581206","https://openalex.org/W6858057904"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"The":[0,81],"standard":[1],"procedures":[2],"for":[3],"detecting":[4],"industrial":[5],"product":[6],"defects":[7,95],"typically":[8],"involve":[9],"collecting":[10],"images,":[11],"labeling":[12,56],"defects,":[13],"and":[14,25,58,73,99,116],"training":[15,92],"models":[16],"through":[17],"supervised":[18],"learning.":[19,64],"This":[20],"process":[21],"is":[22,83],"often":[23],"time-consuming":[24],"laborintensive.":[26],"To":[27],"address":[28],"these":[29],"challenges,":[30],"we":[31,66],"introduce":[32],"the":[33,46,68,97,112,117],"Defect-Aware":[34],"Segment":[35],"Anything":[36],"Model":[37],"(DA-SAM),":[38],"a":[39],"defect":[40,79,101],"detection":[41],"tool":[42],"designed":[43],"to":[44,77],"simplify":[45],"conversion":[47],"of":[48],"box":[49],"labels":[50],"into":[51],"segmentation":[52],"annotations,":[53],"thereby":[54],"reducing":[55],"time":[57],"enabling":[59],"efficient":[60],"zero-":[61],"or":[62],"few-shot":[63],"First,":[65],"fine-tune":[67],"SAM":[69],"model":[70,82],"using":[71],"LoRA":[72],"fine-grained":[74],"bounding":[75],"boxes":[76],"generate":[78],"masks.":[80],"then":[84],"trained":[85],"on":[86,110],"several":[87],"public":[88,114],"datasets.":[89],"A":[90],"two-stage":[91],"approach":[93],"distinguishes":[94],"from":[96],"background":[98],"addresses":[100],"variations.":[102],"Experimental":[103],"results":[104],"demonstrate":[105],"that":[106],"DA-SAM":[107],"performs":[108],"effectively":[109],"both":[111],"MVTecAD":[113],"dataset":[115],"self-collected":[118],"SPTD":[119],"dataset.":[120]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}