乐胖代购免代理版

{"id":"https://openalex.org/W2889721430","doi":"https://doi.org/10.1109/coginfocom.2018.8639888","title":"Analysing object detectors from the perspective of co-occurring object categories","display_name":"Analysing object detectors from the perspective of co-occurring object categories","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2889721430","doi":"https://doi.org/10.1109/coginfocom.2018.8639888","mag":"2889721430"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginfocom.2018.8639888","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/1809.08132","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040231344","display_name":"Csaba Nemes","orcid":null},"institutions":[],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Csaba Nemes","raw_affiliation_strings":["Nokia Bell Labs, Budapest, Hungary"],"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs, Budapest, Hungary","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000853544","display_name":"S\u00e1ndor Jord\u00e1n","orcid":null},"institutions":[],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Sandor Jordan","raw_affiliation_strings":["Nokia Bell Labs, Budapest, Hungary"],"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs, Budapest, Hungary","institution_ids":[]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.07,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":1,"citation_normalized_percentile":{"value":0.194306,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":62,"max":70},"biblio":{"volume":"abs 1512 3385","issue":null,"first_page":"000169","last_page":"000174"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9999,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9999,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.997,"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/representation","display_name":"Representation","score":0.61822796}],"concepts":[{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.7656476},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6709606},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.66729355},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.61822796},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.60017943},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.59202826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5882709},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.55622256},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5306002},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5214914},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5079096},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.44004858},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36823463},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3296882},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.16637984},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07338703},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginfocom.2018.8639888","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.08132","pdf_url":"http://arxiv.org/pdf/1809.08132","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.08132","pdf_url":"http://arxiv.org/pdf/1809.08132","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.48,"display_name":"Reduced inequalities"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":18,"referenced_works":["https://openalex.org/W124653583","https://openalex.org/W1861492603","https://openalex.org/W1981374318","https://openalex.org/W2058091487","https://openalex.org/W2108598243","https://openalex.org/W2110422818","https://openalex.org/W2135130600","https://openalex.org/W2165698076","https://openalex.org/W2194775991","https://openalex.org/W2570343428","https://openalex.org/W2586661295","https://openalex.org/W2613718673","https://openalex.org/W2795918062","https://openalex.org/W2963037989","https://openalex.org/W2964286445","https://openalex.org/W3047986474","https://openalex.org/W4236642187","https://openalex.org/W639708223"],"related_works":["https://openalex.org/W4255837520","https://openalex.org/W4211085505","https://openalex.org/W4205655149","https://openalex.org/W3122478268","https://openalex.org/W2387011115","https://openalex.org/W2366906938","https://openalex.org/W2349391998","https://openalex.org/W2154771632","https://openalex.org/W2084758217","https://openalex.org/W2067317451"],"abstract_inverted_index":{"The":[0],"accuracy":[1],"of":[2,39,94],"state-of-the-art":[3],"Faster":[4],"R-CNN":[5],"and":[6,12,58],"YOLO":[7],"object":[8,33,95],"detectors":[9,66],"are":[10],"evaluated":[11],"compared":[13],"on":[14,28,73],"a":[15,87],"special":[16],"masked":[17],"MS":[18],"COCO":[19],"dataset":[20],"to":[21,53,62,104],"measure":[22],"how":[23],"much":[24],"their":[25],"predictions":[26],"rely":[27],"contextual":[29,74,92],"information":[30,75],"encoded":[31],"at":[32,76],"category":[34,77],"level.":[35],"Category":[36],"level":[37],"representation":[38],"context":[40],"is":[41,97,102],"motivated":[42],"by":[43],"the":[44],"fact":[45],"that":[46,91,101],"it":[47,85],"could":[48],"be":[49,105],"an":[50,98],"adequate":[51],"way":[52],"transfer":[54],"knowledge":[55],"between":[56],"visual":[57],"non-visual":[59],"domains.":[60],"According":[61],"our":[63],"measurements,":[64],"current":[65],"usually":[67],"do":[68],"not":[69],"build":[70],"strong":[71],"dependency":[72],"level,":[78],"however,":[79],"when":[80],"they":[81,83],"does,":[82],"does":[84],"in":[86],"similar":[88],"way,":[89],"suggesting":[90],"dependence":[93],"categories":[96],"independent":[99],"property":[100],"relevant":[103],"transferred.":[106]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2889721430","counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-04-19T03:10:41.621918","created_date":"2018-09-27"}