{"id":"https://openalex.org/W2740912563","doi":"https://doi.org/10.24963/ijcai.2017/315","title":"Discriminative Deep Hashing for Scalable Face Image Retrieval","display_name":"Discriminative Deep Hashing for Scalable Face Image Retrieval","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2740912563","doi":"https://doi.org/10.24963/ijcai.2017/315","mag":"2740912563"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/315","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/315","pdf_url":"https://www.ijcai.org/proceedings/2017/0315.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2017/0315.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101810783","display_name":"Jie Lin","orcid":"https://orcid.org/0000-0002-6618-2930"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Lin","raw_affiliation_strings":["Nanjing University of Science and Technology","School of Computer Science and Engineering, Nanjing University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017096005","display_name":"Zechao Li","orcid":"https://orcid.org/0000-0002-5341-5985"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zechao Li","raw_affiliation_strings":["Nanjing University of Science and Technology","School of Computer Science and Engineering, Nanjing University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035112538","display_name":"Jinhui Tang","orcid":"https://orcid.org/0000-0001-9008-222X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinhui Tang","raw_affiliation_strings":["Nanjing University of Science and Technology","School of Computer Science and Engineering, Nanjing University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5035112538"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":61,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2266","last_page":"2272"},"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":0.9994999766349792,"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":0.9994999766349792,"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/T11448","display_name":"Face recognition and analysis","score":0.9993000030517578,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.994700014591217,"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/hash-function","display_name":"Hash function","score":0.8054174184799194},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7547531127929688},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7398862838745117},{"id":"https://openalex.org/keywords/feature-hashing","display_name":"Feature hashing","score":0.6209570169448853},{"id":"https://openalex.org/keywords/universal-hashing","display_name":"Universal hashing","score":0.5500541925430298},{"id":"https://openalex.org/keywords/dynamic-perfect-hashing","display_name":"Dynamic perfect hashing","score":0.5333703756332397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.517433226108551},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5040968656539917},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.49308106303215027},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4826986789703369},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.46153461933135986},{"id":"https://openalex.org/keywords/double-hashing","display_name":"Double hashing","score":0.3203674554824829},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.2881833612918854},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2225717306137085}],"concepts":[{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.8054174184799194},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7547531127929688},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7398862838745117},{"id":"https://openalex.org/C133667856","wikidata":"https://www.wikidata.org/wiki/Q5439682","display_name":"Feature hashing","level":5,"score":0.6209570169448853},{"id":"https://openalex.org/C116058348","wikidata":"https://www.wikidata.org/wiki/Q846912","display_name":"Universal hashing","level":5,"score":0.5500541925430298},{"id":"https://openalex.org/C122907437","wikidata":"https://www.wikidata.org/wiki/Q5318999","display_name":"Dynamic perfect hashing","level":5,"score":0.5333703756332397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.517433226108551},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5040968656539917},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.49308106303215027},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4826986789703369},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46153461933135986},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.3203674554824829},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.2881833612918854},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2225717306137085},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2017/315","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/315","pdf_url":"https://www.ijcai.org/proceedings/2017/0315.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2017/315","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/315","pdf_url":"https://www.ijcai.org/proceedings/2017/0315.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1110206353","display_name":null,"funder_award_id":"61522203 and 61402228","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1660858375","display_name":null,"funder_award_id":"2014CB347600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G1828425977","display_name":null,"funder_award_id":"973 Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G232447554","display_name":null,"funder_award_id":"61522203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4600227663","display_name":null,"funder_award_id":"61402228","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G466183235","display_name":null,"funder_award_id":"BK20140058","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2740912563.pdf","grobid_xml":"https://content.openalex.org/works/W2740912563.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W1910300841","https://openalex.org/W1913628733","https://openalex.org/W1923967535","https://openalex.org/W1939575207","https://openalex.org/W1974647172","https://openalex.org/W1992371516","https://openalex.org/W1997107867","https://openalex.org/W1998808035","https://openalex.org/W2019464758","https://openalex.org/W2024922353","https://openalex.org/W2038276547","https://openalex.org/W2056935845","https://openalex.org/W2144172034","https://openalex.org/W2145065594","https://openalex.org/W2145287260","https://openalex.org/W2153273131","https://openalex.org/W2163352848","https://openalex.org/W2163605009","https://openalex.org/W2164338181","https://openalex.org/W2187089797","https://openalex.org/W2293597654","https://openalex.org/W2293824885","https://openalex.org/W2464915613","https://openalex.org/W2508837377","https://openalex.org/W2520774990","https://openalex.org/W2530345236","https://openalex.org/W2602143720","https://openalex.org/W2949117887","https://openalex.org/W2964121744","https://openalex.org/W3099206234"],"related_works":["https://openalex.org/W2023326318","https://openalex.org/W2783286101","https://openalex.org/W2921167217","https://openalex.org/W4212830455","https://openalex.org/W2088296667","https://openalex.org/W4301184875","https://openalex.org/W2000284985","https://openalex.org/W2964752363","https://openalex.org/W2802864907","https://openalex.org/W2384172680"],"abstract_inverted_index":{"With":[0],"the":[1,18,58,61,65,93,96,102,108,114,134,138,156],"explosive":[2],"growth":[3],"of":[4,80,95,137],"images":[5],"containing":[6],"faces,":[7],"scalable":[8],"face":[9,51],"image":[10,52],"retrieval":[11],"has":[12,23],"attracted":[13],"increasing":[14],"attention.":[15],"Due":[16],"to":[17,42,85,121,132,145],"amazing":[19],"effectiveness,":[20],"deep":[21],"hashing":[22,27,166],"become":[24],"a":[25,35,71,75,78,118,127],"popular":[26],"method":[28,158],"recently.":[29],"In":[30],"this":[31],"work,":[32],"we":[33],"propose":[34],"new":[36],"Discriminative":[37],"Deep":[38],"Hashing":[39],"(DDH)":[40],"network":[41,56,76,115],"learn":[43],"discriminative":[44,146],"and":[45,64,88,101,113],"compact":[46,123],"hash":[47,111,124,140,147],"codes":[48,112],"for":[49],"large-scale":[50],"retrieval.":[53],"The":[54],"proposed":[55,84,157],"incorporates":[57],"end-to-end":[59],"learning,":[60],"divide-and-encode":[62,119],"module":[63,120],"desired":[66],"discrete":[67],"code":[68],"learning":[69],"into":[70],"unified":[72],"framework.":[73],"Specifically,":[74],"with":[77,163],"stack":[79],"convolution-pooling":[81],"layers":[82],"is":[83,130],"extract":[86],"multi-scale":[87],"robust":[89],"features":[90],"by":[91],"merging":[92],"outputs":[94],"third":[97],"max":[98],"pooling":[99],"layer":[100],"fourth":[103],"convolutional":[104],"layer.":[105],"To":[106],"reduce":[107],"redundancy":[109],"among":[110],"parameters":[116],"simultaneously,":[117],"generate":[122],"codes.":[125,148],"Moreover,":[126],"loss":[128],"function":[129],"introduced":[131],"minimize":[133],"prediction":[135],"errors":[136],"learned":[139],"codes,":[141],"which":[142],"can":[143],"lead":[144],"Extensive":[149],"experiments":[150],"on":[151],"two":[152],"datasets":[153],"demonstrate":[154],"that":[155],"achieves":[159],"superior":[160],"performance":[161],"compared":[162],"some":[164],"state-of-the-art":[165],"methods.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":4}],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2025-10-10T00:00:00"}