{"id":"https://openalex.org/W6926245216","doi":"https://doi.org/10.21227/v1a0-jd82","title":"Specular Highlight Semantic Dataset","display_name":"Specular Highlight Semantic Dataset","publication_year":2025,"publication_date":"2025-03-28","ids":{"openalex":"https://openalex.org/W6926245216","doi":"https://doi.org/10.21227/v1a0-jd82"},"language":"en","primary_location":{"id":"doi:10.21227/v1a0-jd82","is_oa":true,"landing_page_url":"https://doi.org/10.21227/v1a0-jd82","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21227/v1a0-jd82","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Sun, Leyun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Leyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Chen, Jing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10045","display_name":"Organic Electronics and Photovoltaics","score":0.061500001698732376,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10045","display_name":"Organic Electronics and Photovoltaics","score":0.061500001698732376,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11758","display_name":"Organic and Molecular Conductors Research","score":0.04659999907016754,"subfield":{"id":"https://openalex.org/subfields/2504","display_name":"Electronic, Optical and Magnetic Materials"},"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/T11790","display_name":"N-Heterocyclic Carbenes in Organic and Inorganic Chemistry","score":0.04430000111460686,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6632000207901001},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5288000106811523},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5218999981880188},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5109999775886536},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4848000109195709},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4636000096797943},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4494999945163727},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4341000020503998},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4088999927043915}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.79339998960495},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6632000207901001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6323999762535095},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5288000106811523},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5218999981880188},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5109999775886536},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4848000109195709},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4636000096797943},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4494999945163727},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4341000020503998},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4088999927043915},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.376800000667572},{"id":"https://openalex.org/C2985727698","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Semantic annotation","level":3,"score":0.35839998722076416},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3375999927520752},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.32350000739097595},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.32109999656677246},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.31439998745918274},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3122999966144562},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30799999833106995},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.258899986743927},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21227/v1a0-jd82","is_oa":true,"landing_page_url":"https://doi.org/10.21227/v1a0-jd82","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.21227/v1a0-jd82","is_oa":true,"landing_page_url":"https://doi.org/10.21227/v1a0-jd82","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,47,70],"Semantic":[1,31],"Highlight":[2,32],"Mask":[3,33],"Dataset":[4,34],"holds":[5],"significant":[6],"importance":[7],"in":[8,45,100,118],"the":[9,94,115],"field":[10],"of":[11,53,96],"computer":[12],"vision,":[13],"particularly":[14,104],"for":[15,136],"tasks":[16],"such":[17,121],"as":[18,122],"object":[19],"detection,":[20],"image":[21,54,126],"segmentation,":[22],"and":[23,41,64,84,109,128,134],"scene":[24],"understanding.":[25],"This":[26],"paper":[27],"proposes":[28],"a":[29,50],"novel":[30],"designed":[35],"to":[36,67,80],"support":[37],"high-precision":[38],"semantic":[39,62,101],"segmentation":[40,102],"emphasize":[42],"key":[43],"regions":[44],"images.":[46],"dataset":[48,71,91],"encompasses":[49],"diverse":[51],"range":[52],"categories,":[55],"with":[56,77],"finely":[57],"annotated":[58],"highlight":[59],"masks":[60],"assigning":[61],"labels":[63],"saliency":[65],"weights":[66],"each":[68],"pixel.":[69],"construction":[72],"process":[73],"integrates":[74],"automated":[75],"algorithms":[76],"manual":[78],"validation":[79],"ensure":[81],"annotation":[82],"quality":[83],"consistency.":[85],"Experimental":[86],"results":[87],"demonstrate":[88],"that":[89],"this":[90],"significantly":[92],"enhances":[93],"performance":[95],"deep":[97],"learning":[98],"models":[99],"tasks,":[103],"when":[105],"handling":[106],"complex":[107],"backgrounds":[108],"fine-grained":[110],"targets.":[111],"We":[112],"further":[113],"explore":[114],"dataset\u2019s":[116],"potential":[117],"real-world":[119],"applications,":[120],"autonomous":[123],"driving,":[124],"medical":[125],"analysis,":[127],"augmented":[129],"reality,":[130],"providing":[131],"valuable":[132],"resources":[133],"benchmarks":[135],"future":[137],"research.":[138]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}