{"id":"https://openalex.org/W4392248401","doi":"https://doi.org/10.1109/icce59016.2024.10444225","title":"XAI-Enhanced Semantic Segmentation Models for Visual Quality Inspection","display_name":"XAI-Enhanced Semantic Segmentation Models for Visual Quality Inspection","publication_year":2024,"publication_date":"2024-01-06","ids":{"openalex":"https://openalex.org/W4392248401","doi":"https://doi.org/10.1109/icce59016.2024.10444225"},"language":"en","primary_location":{"id":"doi:10.1109/icce59016.2024.10444225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce59016.2024.10444225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5088658925","display_name":"Tobias Clement","orcid":"https://orcid.org/0000-0001-9073-1306"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Tobias Clement","raw_affiliation_strings":["Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg,Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg,Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091003870","display_name":"Truong Thanh Hung Nguyen","orcid":"https://orcid.org/0000-0002-6750-9536"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Truong Thanh Hung Nguyen","raw_affiliation_strings":["Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg,Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg,Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101773285","display_name":"Mohamed Abdelaal","orcid":"https://orcid.org/0009-0006-4561-4761"},"institutions":[{"id":"https://openalex.org/I106938459","display_name":"University of New Brunswick","ror":"https://ror.org/05nkf0n29","country_code":"CA","type":"education","lineage":["https://openalex.org/I106938459"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohamed Abdelaal","raw_affiliation_strings":["University of New Brunswick,Analytics Everywhere Lab,Canada","Analytics Everywhere Lab, University of New Brunswick, Canada"],"affiliations":[{"raw_affiliation_string":"University of New Brunswick,Analytics Everywhere Lab,Canada","institution_ids":["https://openalex.org/I106938459"]},{"raw_affiliation_string":"Analytics Everywhere Lab, University of New Brunswick, Canada","institution_ids":["https://openalex.org/I106938459"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043444646","display_name":"Hung Cao","orcid":"https://orcid.org/0000-0003-0689-3113"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Hung Cao","raw_affiliation_strings":["Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg,Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg,Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5088658925"],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":null,"apc_paid":null,"fwci":1.411,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.81965669,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"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":0.9995999932289124,"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":0.9995999932289124,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9984999895095825,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9927999973297119,"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":0.7630655169487},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6347951889038086},{"id":"https://openalex.org/keywords/visual-inspection","display_name":"Visual inspection","score":0.5807663202285767},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5694944858551025},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5355014801025391},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.46966373920440674},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4076693654060364},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3651820421218872}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7630655169487},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6347951889038086},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.5807663202285767},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5694944858551025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5355014801025391},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46966373920440674},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4076693654060364},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3651820421218872},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce59016.2024.10444225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce59016.2024.10444225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311687","display_name":"Ministry of Education","ror":"https://ror.org/03m01yf64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2194775991","https://openalex.org/W2630837129","https://openalex.org/W2770233088","https://openalex.org/W2772869414","https://openalex.org/W2900198492","https://openalex.org/W2902916563","https://openalex.org/W2963037989","https://openalex.org/W2963811535","https://openalex.org/W2966327746","https://openalex.org/W2972406339","https://openalex.org/W2996889214","https://openalex.org/W3034873438","https://openalex.org/W3035253074","https://openalex.org/W3107327043","https://openalex.org/W3127579051","https://openalex.org/W3186608063","https://openalex.org/W4281259387","https://openalex.org/W4289751568","https://openalex.org/W4298145934","https://openalex.org/W4309730097","https://openalex.org/W4315701371","https://openalex.org/W4322619914","https://openalex.org/W4386363506","https://openalex.org/W4402843978","https://openalex.org/W6739696289","https://openalex.org/W6755523629","https://openalex.org/W6756666686","https://openalex.org/W6782259796"],"related_works":["https://openalex.org/W2781569684","https://openalex.org/W2478098815","https://openalex.org/W4290692565","https://openalex.org/W2371486462","https://openalex.org/W1540410989","https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W2012220638","https://openalex.org/W3186203716","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Visual":[0],"quality":[1,42],"inspection":[2,43],"systems,":[3],"crucial":[4],"in":[5,89],"sectors":[6],"like":[7],"manufacturing":[8],"and":[9,14,31,67,77],"logistics,":[10],"employ":[11],"computer":[12],"vision":[13],"machine":[15],"learning":[16],"for":[17,71],"precise,":[18],"rapid":[19],"defect":[20],"detection.":[21],"However,":[22],"their":[23],"unexplained":[24],"nature":[25],"can":[26],"hinder":[27],"trust,":[28],"error":[29],"identification,":[30],"system":[32],"improvement.":[33],"This":[34],"paper":[35],"presents":[36],"a":[37],"framework":[38],"to":[39,48],"bolster":[40],"visual":[41],"by":[44,75],"using":[45],"CAM-based":[46],"explanations":[47,76],"refine":[49],"semantic":[50],"segmentation":[51],"models.":[52],"Our":[53],"approach":[54],"consists":[55],"of":[56],"1)":[57],"Model":[58,62,72],"Training,":[59],"2)":[60],"XAI-based":[61],"Explanation,":[63],"3)":[64],"XAI":[65],"Evaluation,":[66],"4)":[68],"Annotation":[69],"Augmentation":[70],"Enhancement,":[73],"informed":[74],"expert":[78],"insights.":[79],"Evaluations":[80],"show":[81],"XAI-enhanced":[82],"models":[83],"surpass":[84],"original":[85],"DeepLabv3-ResNet101":[86],"models,":[87],"especially":[88],"intricate":[90],"object":[91],"segmentation.":[92]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}
