{"id":"https://openalex.org/W3204214094","doi":"https://doi.org/10.1145/3467707.3467718","title":"Binary Auto-Encoders Hashing with Manifold Similarity-preserving for Image Retrieval","display_name":"Binary Auto-Encoders Hashing with Manifold Similarity-preserving for Image Retrieval","publication_year":2021,"publication_date":"2021-04-23","ids":{"openalex":"https://openalex.org/W3204214094","doi":"https://doi.org/10.1145/3467707.3467718","mag":"3204214094"},"language":"en","primary_location":{"id":"doi:10.1145/3467707.3467718","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3467707.3467718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th International Conference on Computing and Artificial Intelligence","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/A5055305479","display_name":"Hongmei Tang","orcid":"https://orcid.org/0000-0002-7147-8103"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongmei Tang","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078693770","display_name":"Liming Xu","orcid":"https://orcid.org/0000-0002-0671-8182"},"institutions":[{"id":"https://openalex.org/I16351329","display_name":"China West Normal University","ror":"https://ror.org/04s99y476","country_code":"CN","type":"education","lineage":["https://openalex.org/I16351329"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liming Xu","raw_affiliation_strings":["China West Normal University, China"],"affiliations":[{"raw_affiliation_string":"China West Normal University, China","institution_ids":["https://openalex.org/I16351329"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100656785","display_name":"Xianhua Zeng","orcid":"https://orcid.org/0000-0001-5892-2372"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianhua Zeng","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055305479"],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":0.0961,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40214052,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2019","issue":null,"first_page":"76","last_page":"82"},"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":1.0,"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":1.0,"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":0.9882000088691711,"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":0.8110121488571167},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6004825830459595},{"id":"https://openalex.org/keywords/binary-code","display_name":"Binary code","score":0.5987200736999512},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5713915228843689},{"id":"https://openalex.org/keywords/double-hashing","display_name":"Double hashing","score":0.5371874570846558},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.47940775752067566},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4639401435852051},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46047013998031616},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.45402437448501587},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43330809473991394},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3888450860977173},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.32044345140457153},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3021344542503357},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.14865991473197937}],"concepts":[{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.8110121488571167},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6004825830459595},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.5987200736999512},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5713915228843689},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.5371874570846558},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.47940775752067566},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4639401435852051},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46047013998031616},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.45402437448501587},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43330809473991394},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3888450860977173},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.32044345140457153},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3021344542503357},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.14865991473197937},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3467707.3467718","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3467707.3467718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th International Conference on Computing and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1835419070","https://openalex.org/W1974647172","https://openalex.org/W2007972815","https://openalex.org/W2029205712","https://openalex.org/W2143321506","https://openalex.org/W2153273131","https://openalex.org/W2602143720","https://openalex.org/W2786585376","https://openalex.org/W2896826707","https://openalex.org/W2929226556","https://openalex.org/W2940631331","https://openalex.org/W3017281870","https://openalex.org/W3099385964","https://openalex.org/W3099677434","https://openalex.org/W4244531973"],"related_works":["https://openalex.org/W2069568684","https://openalex.org/W3019245231","https://openalex.org/W1984081611","https://openalex.org/W2376661060","https://openalex.org/W2948607823","https://openalex.org/W113683524","https://openalex.org/W4387251676","https://openalex.org/W2088296667","https://openalex.org/W4385261619","https://openalex.org/W93624718"],"abstract_inverted_index":{"By":[0],"minimizing":[1],"reconstruction":[2,25],"loss,":[3],"binary":[4,61],"auto-encoders":[5,62],"algorithm":[6,21,58,73],"makes":[7],"the":[8,12,16,20,24,30,36,69,75,78,91,97,104,110,117,122,125,131,135,139,149,176],"hash":[9,46,80,87,105,118,127],"codes":[10,81,106,119,128],"keep":[11,90],"important":[13],"information":[14,34,95,153],"of":[15,77,96,134],"original":[17,37,98],"input.":[18],"However,":[19],"only":[22],"considers":[23],"loss":[26,113],"and":[27,124,170],"doesn't":[28],"consider":[29],"local":[31,92,150],"geometric":[32,93,151],"structure":[33,94,152],"between":[35,116],"data,":[38],"which":[39,89],"is":[40,82,114],"bad":[41],"for":[42,74],"learning":[43,132],"high":[44],"quality":[45],"functions.":[47],"Therefore,":[48],"in":[49],"this":[50],"paper,":[51],"we":[52],"propose":[53],"a":[54,108],"new":[55],"image":[56,186],"retrieval":[57,187],"based":[59],"on":[60,163],"hashing":[63],"with":[64,183],"manifold":[65,111],"similarity-preserving":[66,112],"(MSP-BAH).":[67],"First,":[68],"supervised":[70],"Laplacian":[71],"eigenmaps":[72],"generation":[76],"referenced":[79,86,126],"used":[83],"to":[84,129],"generate":[85],"codes,":[88],"input":[99],"data.":[100],"Then":[101],"by":[102,121],"using":[103],"as":[107,155,157],"reference,":[109],"constructed":[115],"generated":[120],"encoder":[123],"guide":[130],"process":[133],"model,":[136],"so":[137],"that":[138,175],"MSP-BAH":[140,177],"model":[141],"can":[142],"provide":[143],"strong":[144],"characterization":[145],"ability":[146],"while":[147],"keeping":[148],"unchanged":[154],"much":[156],"possible.":[158],"We":[159],"perform":[160],"some":[161],"experiments":[162],"three":[164],"benchmark":[165],"datasets,":[166],"i.e.,":[167],"CIFAR10,":[168],"MNIST,":[169],"NUS-WIDE.":[171],"The":[172],"results":[173],"show":[174],"method":[178],"has":[179],"better":[180],"performance":[181],"comparing":[182],"several":[184],"existing":[185],"methods.":[188]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
