{"id":"https://openalex.org/W4392902726","doi":"https://doi.org/10.1109/tnnls.2024.3363163","title":"Locating Target Regions for Image Retrieval in an Unsupervised Manner","display_name":"Locating Target Regions for Image Retrieval in an Unsupervised Manner","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392902726","doi":"https://doi.org/10.1109/tnnls.2024.3363163","pmid":"https://pubmed.ncbi.nlm.nih.gov/38498736"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3363163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3363163","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5012744134","display_name":"Bo-Jian Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo-Jian Zhang","raw_affiliation_strings":["College of Computer Science and Engineering, Guangxi Normal University, Guilin, China"],"raw_orcid":"https://orcid.org/0000-0001-9980-6263","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033694378","display_name":"Guanghai Liu","orcid":"https://orcid.org/0000-0002-1558-2694"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guang-Hai Liu","raw_affiliation_strings":["College of Computer Science and Engineering, Guangxi Normal University, Guilin, China"],"raw_orcid":"https://orcid.org/0000-0002-1558-2694","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091320821","display_name":"Zuoyong Li","orcid":"https://orcid.org/0000-0003-0952-9915"},"institutions":[{"id":"https://openalex.org/I354108","display_name":"Minjiang University","ror":"https://ror.org/00s7tkw17","country_code":"CN","type":"education","lineage":["https://openalex.org/I354108"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuo-Yong Li","raw_affiliation_strings":["College of Computer and Control Engineering, Minjiang University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0952-9915","affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Minjiang University, Fuzhou, China","institution_ids":["https://openalex.org/I354108"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025660318","display_name":"Shuxiang Song","orcid":"https://orcid.org/0000-0003-0280-2640"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shu-Xiang Song","raw_affiliation_strings":["College of Electronic Engineering, Guangxi Normal University, Guilin, China"],"raw_orcid":"https://orcid.org/0000-0003-0280-2640","affiliations":[{"raw_affiliation_string":"College of Electronic Engineering, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4617,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.56381117,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"36","issue":"3","first_page":"4664","last_page":"4676"},"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":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10824","display_name":"Image Retrieval and Classification 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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9976000189781189,"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":0.8060812950134277},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7657911777496338},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7131443023681641},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6525614857673645},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.592322826385498},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.5910578966140747},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.47045695781707764},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.45006927847862244},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.41835829615592957},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41547706723213196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8060812950134277},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7657911777496338},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7131443023681641},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6525614857673645},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.592322826385498},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.5910578966140747},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.47045695781707764},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.45006927847862244},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.41835829615592957},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41547706723213196},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3363163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3363163","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38498736","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38498736","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1191591178","display_name":null,"funder_award_id":"62266008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7038125391","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u8840\u6db2\u767d\u7ec6\u80de\u5206\u5272\u4e0e\u5206\u7c7b\u7814\u7a76","funder_award_id":"61972187","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8525241642","display_name":null,"funder_award_id":"62366006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W204268067","https://openalex.org/W1679894842","https://openalex.org/W2001773889","https://openalex.org/W2100398441","https://openalex.org/W2108598243","https://openalex.org/W2117539524","https://openalex.org/W2141362318","https://openalex.org/W2148809531","https://openalex.org/W2151103935","https://openalex.org/W2188770163","https://openalex.org/W2194775991","https://openalex.org/W2204975001","https://openalex.org/W2295107390","https://openalex.org/W2295537791","https://openalex.org/W2340690086","https://openalex.org/W2479109623","https://openalex.org/W2499468060","https://openalex.org/W2620629206","https://openalex.org/W2750727695","https://openalex.org/W2751825910","https://openalex.org/W2796108154","https://openalex.org/W2802862847","https://openalex.org/W2807149475","https://openalex.org/W2897078023","https://openalex.org/W2897464384","https://openalex.org/W2902101981","https://openalex.org/W2949146206","https://openalex.org/W2949741748","https://openalex.org/W2963090248","https://openalex.org/W2963154697","https://openalex.org/W2963420686","https://openalex.org/W2963436667","https://openalex.org/W2963588253","https://openalex.org/W2967457289","https://openalex.org/W2982392870","https://openalex.org/W2986992616","https://openalex.org/W3001091189","https://openalex.org/W3016451726","https://openalex.org/W3035502324","https://openalex.org/W3036999909","https://openalex.org/W3099250063","https://openalex.org/W3109923227","https://openalex.org/W3110536152","https://openalex.org/W3117229751","https://openalex.org/W3128099838","https://openalex.org/W3135201010","https://openalex.org/W3136761610","https://openalex.org/W3137228985","https://openalex.org/W3138366398","https://openalex.org/W3138516171","https://openalex.org/W3161187512","https://openalex.org/W3165938948","https://openalex.org/W3166041482","https://openalex.org/W3167976421","https://openalex.org/W3176398328","https://openalex.org/W3179826082","https://openalex.org/W3185141858","https://openalex.org/W3188250593","https://openalex.org/W3203778378","https://openalex.org/W4205687942","https://openalex.org/W4210807968","https://openalex.org/W4210932445","https://openalex.org/W4286910290","https://openalex.org/W4287367114","https://openalex.org/W4298625452","https://openalex.org/W4319300245","https://openalex.org/W6637373629","https://openalex.org/W6685522000","https://openalex.org/W6790570412","https://openalex.org/W6790741352","https://openalex.org/W6802648153"],"related_works":["https://openalex.org/W4296209631","https://openalex.org/W2561617217","https://openalex.org/W2025378473","https://openalex.org/W4391621807","https://openalex.org/W2355801475","https://openalex.org/W4206659427","https://openalex.org/W2170062176","https://openalex.org/W2148135840","https://openalex.org/W106004901","https://openalex.org/W2123991572"],"abstract_inverted_index":{"Image":[0],"retrieval":[1,60,183,187,197],"performance":[2,162],"can":[3,70,177],"be":[4,178],"improved":[5],"by":[6,138,165],"training":[7],"a":[8,56,88,114,121,147,171],"convolutional":[9],"neural":[10],"network":[11],"(CNN)":[12],"model":[13],"with":[14],"annotated":[15,27],"data":[16,28],"to":[17,39,94,126,152,181,185,223],"facilitate":[18],"accurate":[19,41],"localization":[20,42,66,107],"of":[21,43,98,109,136,195],"target":[22,44,64,73,101,130],"regions.":[23,102],"However,":[24],"obtaining":[25],"sufficiently":[26],"is":[29,37,170],"expensive":[30],"and":[31,143,173],"impractical":[32],"in":[33,46,100],"real":[34],"settings.":[35],"It":[36,69,132],"challenging":[38],"achieve":[40],"regions":[45,74],"an":[47],"unsupervised":[48,58,63,226],"manner.":[49],"To":[50],"address":[51,95],"this":[52],"problem,":[53],"we":[54,86,119,145],"propose":[55,87,120,146],"new":[57],"image":[59,182,196],"method":[61,81,93,125,151,175,213],"named":[62,156],"region":[65],"(UTRL)":[67],"descriptors.":[68],"precisely":[71],"locate":[72],"without":[75],"supervisory":[76],"information":[77],"or":[78],"learning.":[79],"Our":[80],"contains":[82],"three":[83],"highlights:":[84],"1)":[85],"novel":[89],"zero-label":[90,115],"transfer":[91],"learning":[92],"the":[96,105,134,161,193],"problem":[97],"co-localization":[99],"This":[103,189],"enhances":[104],"potential":[106],"ability":[108],"pretrained":[110],"CNN":[111],"models":[112],"through":[113],"data-driven":[116],"approach;":[117],"2)":[118],"multiscale":[122],"attention":[123],"accumulation":[124],"accurately":[127],"extract":[128],"distinguishable":[129],"features.":[131,202],"distinguishes":[133],"importance":[135],"features":[137],"using":[139],"local":[140],"Gaussian":[141],"weights;":[142],"3)":[144],"simple":[148],"yet":[149],"effective":[150],"reduce":[153],"vector":[154,201],"dimensionality,":[155],"twice-PCA-whitening":[157],"(TPW),":[158],"which":[159],"reduces":[160],"degradation":[163],"caused":[164],"feature":[166],"compression.":[167],"Notably,":[168],"TPW":[169],"robust":[172],"general":[174],"that":[176,211],"widely":[179],"applied":[180],"tasks":[184],"improve":[186],"performance.":[188],"work":[190],"also":[191],"facilitates":[192],"development":[194],"based":[198],"on":[199,205],"short":[200],"Extensive":[203],"experiments":[204],"six":[206],"popular":[207],"benchmark":[208],"datasets":[209],"demonstrate":[210],"our":[212],"achieves":[214],"about":[215],"7%":[216],"greater":[217],"mean":[218],"average":[219],"precision":[220],"(mAP)":[221],"compared":[222],"existing":[224],"state-of-the-art":[225],"methods.":[227]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}