{"id":"https://openalex.org/W4408861362","doi":"https://doi.org/10.1109/icce63647.2025.10929914","title":"Semantic Edge Detection with ConvNeXt and Bi-Directional MLA","display_name":"Semantic Edge Detection with ConvNeXt and Bi-Directional MLA","publication_year":2025,"publication_date":"2025-01-11","ids":{"openalex":"https://openalex.org/W4408861362","doi":"https://doi.org/10.1109/icce63647.2025.10929914"},"language":"en","primary_location":{"id":"doi:10.1109/icce63647.2025.10929914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce63647.2025.10929914","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/A5107937805","display_name":"G. N. Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Gwangsoo Kim","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024723558","display_name":"Hyuk\u2010Jae Lee","orcid":"https://orcid.org/0000-0001-6811-9647"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyuk-Jae Lee","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032850681","display_name":"Hyunmin Jung","orcid":"https://orcid.org/0000-0001-8216-5842"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunmin Jung","raw_affiliation_strings":["Seoul National University of Science and Technology,Department of Smart ICT Convergence Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University of Science and Technology,Department of Smart ICT Convergence Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I118373667"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5107937805"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02787344,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T10028","display_name":"Topic Modeling","score":0.9492999911308289,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9492999911308289,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9463000297546387,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.930899977684021,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7242139577865601},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4998764991760254},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3339812159538269}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7242139577865601},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4998764991760254},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3339812159538269}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce63647.2025.10929914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce63647.2025.10929914","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":0.4000000059604645,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1920001376","display_name":null,"funder_award_id":"RS-2023-00229330","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2805848721","https://openalex.org/W3138516171","https://openalex.org/W3192537953","https://openalex.org/W4246233237","https://openalex.org/W4312710812","https://openalex.org/W4323266622","https://openalex.org/W4386076493","https://openalex.org/W4400230089"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"This":[0,26],"paper":[1,87],"focuses":[2],"on":[3,8],"semantic":[4,27,64],"edge":[5,28,65,127],"detection":[6,29,128],"based":[7],"physical":[9,62],"properties":[10],"(cause":[11],"of":[12,61,75,117],"occurrence),":[13],"which":[14],"classifies":[15],"edges":[16],"into":[17],"four":[18],"classes:":[19],"reflectance,":[20],"illumination,":[21],"normal,":[22],"and":[23,36,77,115,120,123,129],"depth":[24],"edges.":[25],"is":[30,55,93],"widely":[31],"used":[32],"in":[33,73,112],"consumer":[34],"electronics":[35],"industrial":[37],"manufacturing":[38],"as":[39],"a":[40,49],"complement":[41],"to":[42,57,80,106],"computer":[43],"vision":[44],"technology.":[45],"In":[46,84],"this":[47,86],"paper,":[48],"convolutional":[50],"neural":[51],"network":[52,54,70],"(CNN)-based":[53],"proposed":[56,68,97,100],"improve":[58],"the":[59,81,89,96,107],"performance":[60,104],"property-based":[63],"detection.":[66],"The":[67,99],"CNN-based":[69],"has":[71],"advantages":[72],"terms":[74],"memory":[76],"speed":[78],"compared":[79,105],"Transformer-based":[82],"approaches.":[83],"addition,":[85],"analyzes":[88],"loss":[90],"function":[91],"that":[92],"effective":[94],"for":[95],"network.":[98],"method":[101],"shows":[102],"superior":[103],"previous":[108],"state-of-the-art,":[109],"with":[110],"improvements":[111],"ODS,":[113],"OIS,":[114],"AP":[116],"1.1%,":[118],"4.7%,":[119],"2.7%,":[121],"respectively,":[122],"qualitatively":[124],"demonstrates":[125],"improved":[126],"classification":[130],"performance.":[131]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}