{"id":"https://openalex.org/W4317418863","doi":"https://doi.org/10.1109/gcce56475.2022.10014104","title":"Semantic Segmentation of Equirectangular Images with UniFuse","display_name":"Semantic Segmentation of Equirectangular Images with UniFuse","publication_year":2022,"publication_date":"2022-10-18","ids":{"openalex":"https://openalex.org/W4317418863","doi":"https://doi.org/10.1109/gcce56475.2022.10014104"},"language":"en","primary_location":{"id":"doi:10.1109/gcce56475.2022.10014104","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/gcce56475.2022.10014104","pdf_url":null,"source":{"id":"https://openalex.org/S4363607800","display_name":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5085539789","display_name":"Atsushi Yokota","orcid":"https://orcid.org/0000-0003-1806-5067"},"institutions":[{"id":"https://openalex.org/I57930482","display_name":"Hiroshima City University","ror":"https://ror.org/001et4e78","country_code":"JP","type":"education","lineage":["https://openalex.org/I57930482"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsushi Yokota","raw_affiliation_strings":["Hiroshima City University,Graduate School of Information Sciences,Hiroshima,Japan","Graduate School of Information Sciences, Hiroshima City University, Hiroshima, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hiroshima City University,Graduate School of Information Sciences,Hiroshima,Japan","institution_ids":["https://openalex.org/I57930482"]},{"raw_affiliation_string":"Graduate School of Information Sciences, Hiroshima City University, Hiroshima, Japan","institution_ids":["https://openalex.org/I57930482"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088172355","display_name":"Shigang Li","orcid":"https://orcid.org/0000-0003-0022-7865"},"institutions":[{"id":"https://openalex.org/I57930482","display_name":"Hiroshima City University","ror":"https://ror.org/001et4e78","country_code":"JP","type":"education","lineage":["https://openalex.org/I57930482"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shigang Li","raw_affiliation_strings":["Hiroshima City University,Graduate School of Information Sciences,Hiroshima,Japan","Graduate School of Information Sciences, Hiroshima City University, Hiroshima, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hiroshima City University,Graduate School of Information Sciences,Hiroshima,Japan","institution_ids":["https://openalex.org/I57930482"]},{"raw_affiliation_string":"Graduate School of Information Sciences, Hiroshima City University, Hiroshima, Japan","institution_ids":["https://openalex.org/I57930482"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I57930482"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"523","last_page":"524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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/T12549","display_name":"Image and Object Detection Techniques","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/T10638","display_name":"Optical measurement and interference techniques","score":0.9980999827384949,"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":0.8097013235092163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7805581092834473},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7493561506271362},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6269989013671875},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.592882513999939},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5437189340591431},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5244600772857666},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4620939791202545},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4615021347999573},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3562469482421875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8097013235092163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7805581092834473},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7493561506271362},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6269989013671875},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.592882513999939},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5437189340591431},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5244600772857666},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4620939791202545},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4615021347999573},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3562469482421875},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce56475.2022.10014104","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/gcce56475.2022.10014104","pdf_url":null,"source":{"id":"https://openalex.org/S4363607800","display_name":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2095705004","https://openalex.org/W2586114507","https://openalex.org/W3034728336","https://openalex.org/W3126573238","https://openalex.org/W3131795671","https://openalex.org/W6674330103","https://openalex.org/W6733367512"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W3011384228","https://openalex.org/W4313052709","https://openalex.org/W2945274617","https://openalex.org/W3199300986","https://openalex.org/W4298131179","https://openalex.org/W2375430703","https://openalex.org/W4323893507"],"abstract_inverted_index":{"UniFuse":[0,22],"is":[1],"a":[2],"neural":[3,39],"network":[4],"that":[5],"has":[6],"achieved":[7],"high":[8],"accuracy":[9],"in":[10],"generating":[11],"depth":[12],"maps":[13],"for":[14],"equirectangular":[15,28],"images.":[16],"In":[17],"this":[18],"paper,":[19],"we":[20],"modified":[21],"to":[23],"semantic":[24],"segmentation":[25],"task":[26],"of":[27,47],"images":[29],"and":[30],"carried":[31],"out":[32],"comparative":[33],"experiments":[34],"with":[35],"the":[36,45],"popular":[37],"UNet":[38],"network.":[40],"The":[41],"experimental":[42],"results":[43],"showed":[44],"effectiveness":[46],"our":[48],"proposed":[49],"method.":[50]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
