{"id":"https://openalex.org/W2890448425","doi":"https://doi.org/10.1109/icip.2018.8451486","title":"Gated Square-Root Pooling for Image Instance Retrieval","display_name":"Gated Square-Root Pooling for Image Instance Retrieval","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2890448425","doi":"https://doi.org/10.1109/icip.2018.8451486","mag":"2890448425"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451486","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-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/A5061136335","display_name":"Ziqian Chen","orcid":"https://orcid.org/0000-0003-2514-6906"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziqian Chen","raw_affiliation_strings":["Peking University, Beijing, Beijing, CN"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030005076","display_name":"Jie Lin","orcid":"https://orcid.org/0000-0002-8971-0660"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jie Lin","raw_affiliation_strings":["IR, Singapore"],"affiliations":[{"raw_affiliation_string":"IR, Singapore","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103502228","display_name":"Vijay Chandrasekhar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vijay Chandrasekhar","raw_affiliation_strings":["IR, Singapore","NTU, Singapore"],"affiliations":[{"raw_affiliation_string":"IR, Singapore","institution_ids":[]},{"raw_affiliation_string":"NTU, Singapore","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024879728","display_name":"Ling\u2010Yu Duan","orcid":"https://orcid.org/0000-0002-4491-2023"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling-Yu Duan","raw_affiliation_strings":["Peking University, Beijing, Beijing, CN"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061136335"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":1.0446,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.82461555,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1982","last_page":"1986"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9955999851226807,"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/pooling","display_name":"Pooling","score":0.9147496223449707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7323434352874756},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6859650611877441},{"id":"https://openalex.org/keywords/square-root","display_name":"Square root","score":0.5853134393692017},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5587806105613708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5329172611236572},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5294138193130493},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.519575834274292},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48023563623428345},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45361968874931335},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.4309287667274475},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42987293004989624},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4259885549545288},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35222530364990234},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3491196036338806},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19979771971702576}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.9147496223449707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7323434352874756},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6859650611877441},{"id":"https://openalex.org/C11577676","wikidata":"https://www.wikidata.org/wiki/Q134237","display_name":"Square root","level":2,"score":0.5853134393692017},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5587806105613708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5329172611236572},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5294138193130493},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.519575834274292},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48023563623428345},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45361968874931335},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4309287667274475},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42987293004989624},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4259885549545288},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35222530364990234},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3491196036338806},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19979771971702576},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2018.8451486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451486","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W204268067","https://openalex.org/W1524680991","https://openalex.org/W1556531089","https://openalex.org/W1686810756","https://openalex.org/W1975517671","https://openalex.org/W1979931042","https://openalex.org/W2012592962","https://openalex.org/W2044284589","https://openalex.org/W2045143396","https://openalex.org/W2071027807","https://openalex.org/W2102605133","https://openalex.org/W2103924867","https://openalex.org/W2108598243","https://openalex.org/W2128017662","https://openalex.org/W2141362318","https://openalex.org/W2148809531","https://openalex.org/W2149357475","https://openalex.org/W2151103935","https://openalex.org/W2157364932","https://openalex.org/W2163605009","https://openalex.org/W2174726731","https://openalex.org/W2179042386","https://openalex.org/W2194775991","https://openalex.org/W2204975001","https://openalex.org/W2295537791","https://openalex.org/W2336302573","https://openalex.org/W2340690086","https://openalex.org/W2544587078","https://openalex.org/W2620629206","https://openalex.org/W2962835968","https://openalex.org/W2963125676","https://openalex.org/W2963919294","https://openalex.org/W6608313692","https://openalex.org/W6631498818","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6685522000","https://openalex.org/W6688902765","https://openalex.org/W6704508018"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W3103989898","https://openalex.org/W4287804464","https://openalex.org/W2965546495","https://openalex.org/W803346624"],"abstract_inverted_index":{"Recently":[0],"Convolutional":[1],"Neural":[2],"Networks":[3],"(CNNs)":[4],"have":[5],"achieved":[6],"great":[7],"success":[8],"in":[9,98,121],"different":[10,40,119],"fields":[11],"including":[12],"image":[13,61],"instance":[14,62,102],"retrieval.":[15,63,103],"However":[16],"traditional":[17],"global":[18,54],"pooling":[19,56,75,95],"approaches":[20],"fail":[21],"to":[22,90],"capture":[23],"all":[24],"possible":[25],"discriminative":[26],"information":[27,83],"of":[28,38,53,82,101,118],"CNN":[29,58],"activations":[30,33,59],"and":[31,87,93],"treat":[32],"over":[34,57,84,139],"channels":[35],"equally":[36],"regardless":[37],"the":[39,50,99,116,133],"importance":[41],"between":[42],"channels.":[43],"In":[44],"this":[45],"work,":[46],"we":[47,69,105],"focus":[48],"on":[49,127],"mentioned":[51],"problem":[52],"feature":[55],"for":[60],"We":[64],"make":[65],"two":[66],"contributions.":[67],"First,":[68],"introduce":[70],"a":[71,111],"channel-wise":[72],"SQUare-root":[73],"(SQU)":[74],"(2-norm)":[76],"approach,":[77],"which":[78],"makes":[79],"better":[80],"use":[81],"activation":[85],"maps":[86],"is":[88],"superior":[89],"Average":[91],"(1-norm)":[92],"Max":[94],"(infinity":[96],"norm),":[97],"context":[100],"Second,":[104],"further":[106],"improve":[107],"SQU":[108],"by":[109],"learning":[110],"gating":[112],"function":[113],"that":[114,132],"weights":[115],"contributions":[117],"channels,":[120],"an":[122],"end-to-end":[123],"manner.":[124],"Extensive":[125],"experiments":[126],"6":[128],"benchmark":[129],"datasets":[130],"show":[131],"proposed":[134],"strategies":[135],"achieve":[136],"considerable":[137],"improvements":[138],"state-of-the-art.":[140]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
