{"id":"https://openalex.org/W4295832435","doi":"https://doi.org/10.1109/tai.2022.3206180","title":"Group Ensemble Block: Subspace Diversity Improves Coarse-to-Fine Image Retrieval","display_name":"Group Ensemble Block: Subspace Diversity Improves Coarse-to-Fine Image Retrieval","publication_year":2022,"publication_date":"2022-09-13","ids":{"openalex":"https://openalex.org/W4295832435","doi":"https://doi.org/10.1109/tai.2022.3206180"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2022.3206180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2022.3206180","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-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/A5088406193","display_name":"Zhihao Zhao","orcid":"https://orcid.org/0000-0001-6135-3510"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhihao Zhao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057883383","display_name":"Shangqing Zhao","orcid":"https://orcid.org/0000-0001-8543-2977"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shangqing Zhao","raw_affiliation_strings":["Department of Computer Science, University of Oklahoma, Norman, OK, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Oklahoma, Norman, OK, USA","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017174019","display_name":"Samuel Cheng","orcid":"https://orcid.org/0000-0002-5439-1137"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samuel Cheng","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA","institution_ids":["https://openalex.org/I8692664"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5088406193"],"corresponding_institution_ids":["https://openalex.org/I8692664"],"apc_list":null,"apc_paid":null,"fwci":0.302,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.54126987,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"4","issue":"1","first_page":"60","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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":0.9991999864578247,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9976999759674072,"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/block","display_name":"Block (permutation group theory)","score":0.7649194002151489},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7567552328109741},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.669223427772522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6510026454925537},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6481567025184631},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.5726683735847473},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5646084547042847},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4874415695667267},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4751279950141907},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.4431923031806946},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.41292011737823486},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40098506212234497},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3442864716053009},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26804929971694946}],"concepts":[{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.7649194002151489},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7567552328109741},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.669223427772522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6510026454925537},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6481567025184631},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.5726683735847473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5646084547042847},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4874415695667267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4751279950141907},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.4431923031806946},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.41292011737823486},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40098506212234497},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3442864716053009},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26804929971694946},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2022.3206180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2022.3206180","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"},{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2095705004","https://openalex.org/W2096733369","https://openalex.org/W2108598243","https://openalex.org/W2113242816","https://openalex.org/W2120240539","https://openalex.org/W2144935315","https://openalex.org/W2194775991","https://openalex.org/W2336302573","https://openalex.org/W2340690086","https://openalex.org/W2470446127","https://openalex.org/W2549858646","https://openalex.org/W2605102252","https://openalex.org/W2622263826","https://openalex.org/W2656999302","https://openalex.org/W2885201931","https://openalex.org/W2885563408","https://openalex.org/W2948077755","https://openalex.org/W2949736877","https://openalex.org/W2962723992","https://openalex.org/W2963113119","https://openalex.org/W2963842104","https://openalex.org/W2998508940","https://openalex.org/W3034345981","https://openalex.org/W3035524453","https://openalex.org/W3109241881","https://openalex.org/W3118608800","https://openalex.org/W3171007011","https://openalex.org/W3178565749","https://openalex.org/W4295224294","https://openalex.org/W6638667902","https://openalex.org/W6674330103","https://openalex.org/W6680962578","https://openalex.org/W6725762072","https://openalex.org/W6730323794","https://openalex.org/W6739531988","https://openalex.org/W6739622702","https://openalex.org/W6774314701","https://openalex.org/W6779326418","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2094490861","https://openalex.org/W1981866886","https://openalex.org/W2052615004","https://openalex.org/W2046975922","https://openalex.org/W4361733484","https://openalex.org/W4256395896","https://openalex.org/W2057416691","https://openalex.org/W1760344465","https://openalex.org/W2770076983","https://openalex.org/W4205397888"],"abstract_inverted_index":{"The":[0,43],"random":[1],"subspace":[2],"method":[3],"is":[4,71,150,203],"an":[5],"ensemble":[6,41,45,94,148,182],"learning":[7],"technique":[8],"of":[9,21,28,66,77,90,120],"great":[10],"potential.":[11],"However,":[12],"its":[13,18,22],"popularity":[14],"does":[15],"not":[16],"match":[17],"potential":[19],"because":[20],"prohibitive":[23],"cost":[24],"and":[25,80,108,131,161,164,191,210,218],"the":[26,38,48,60,75,92,105,179,185,189,195,201],"lack":[27],"plug-and-play":[29],"reusable":[30],"modules.":[31],"To":[32],"fill":[33],"this":[34],"gap,":[35],"we":[36],"propose":[37],"random-subspace-based":[39],"group":[40,147,181],"block.":[42],"proposed":[44,93,180],"block":[46,95,149,183],"increases":[47],"diversity":[49,61],"among":[50,62],"subspaces":[51],"by":[52,73,99,104,112],"masking":[53],"each":[54],"sampled":[55],"subspace.":[56,117],"It":[57],"also":[58,166],"utilizes":[59],"a":[63,137],"large":[64],"number":[65],"subspaces,":[67],"e.g.,":[68],"1024,":[69],"which":[70],"facilitated":[72],"combining":[74],"advantages":[76],"both":[78],"averaging":[79],"concatenating":[81],"strategies":[82],"for":[83,115,155,169,194],"merging":[84],"different":[85],"subspaces'":[86],"outcomes.":[87],"In":[88,118],"terms":[89,119],"cost,":[91],"contributes":[96],"few":[97],"parameters":[98],"parameter":[100],"sharing,":[101],"negligible":[102],"computations":[103],"linear":[106,138],"transformation,":[107],"fast":[109],"running":[110],"speed":[111],"parallel":[113],"processing":[114],"every":[116,124],"reusability,":[121],"it":[122],"encapsulates":[123],"necessary":[125],"step":[126],"in":[127,140],"one":[128],"small":[129],"block,":[130],"can":[132,165],"be":[133,167],"interchangeably":[134],"used":[135],"as":[136,159,173],"layer":[139],"neural":[141],"networks.":[142],"We":[143],"show":[144,177],"that":[145,178],"our":[146],"complementary":[151],"to":[152],"existing":[153],"methods":[154],"image":[156,174,197],"retrieval":[157,198],"such":[158,172],"class-level":[160],"instance-level":[162],"discrimination,":[163],"deployed":[168],"other":[170],"tasks":[171],"classification.":[175],"Experiments":[176],"achieves":[184],"state-of-the-art":[186],"accuracy":[187],"on":[188],"CIFAR-100":[190],"ImageNet":[192],"datasets":[193],"coarse-to-fine":[196],"problem,":[199],"where":[200],"model":[202],"trained":[204],"with":[205,212],"coarse-level":[206],"annotation":[207],"(e.g.,":[208,215],"trees)":[209],"evaluated":[211],"fine-grained":[213],"category":[214],"maple":[216],"trees":[217],"oak":[219],"trees).":[220]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}