{"id":"https://openalex.org/W3116092226","doi":"https://doi.org/10.1145/3430199.3430225","title":"Deep Hashing Network Based on Split Channels for Hybrid-Source Remote Sensing Image Retrieval","display_name":"Deep Hashing Network Based on Split Channels for Hybrid-Source Remote Sensing Image Retrieval","publication_year":2020,"publication_date":"2020-06-26","ids":{"openalex":"https://openalex.org/W3116092226","doi":"https://doi.org/10.1145/3430199.3430225","mag":"3116092226"},"language":"en","primary_location":{"id":"doi:10.1145/3430199.3430225","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3430199.3430225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 3rd International Conference on Artificial Intelligence and Pattern Recognition","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/A5053368138","display_name":"Salayidin Sirajidin","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Salayidin Sirajidin","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011090035","display_name":"Hong Huo","orcid":"https://orcid.org/0000-0002-2862-9455"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Huo","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101615935","display_name":"Tao Fang","orcid":"https://orcid.org/0000-0002-8277-2551"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Fang","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5053368138"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.15649997,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"126","last_page":"132"},"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":0.9962000250816345,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7520561218261719},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6457977294921875},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6417254209518433},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4749232232570648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4053935706615448},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09647756814956665}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7520561218261719},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6457977294921875},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6417254209518433},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4749232232570648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4053935706615448},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09647756814956665}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3430199.3430225","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3430199.3430225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 3rd International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1974647172","https://openalex.org/W1989316905","https://openalex.org/W2091280333","https://openalex.org/W2120782420","https://openalex.org/W2163605009","https://openalex.org/W2203543769","https://openalex.org/W2207125444","https://openalex.org/W2580615709","https://openalex.org/W2763822693","https://openalex.org/W2798834175","https://openalex.org/W2808376087","https://openalex.org/W2919115771","https://openalex.org/W2964280870","https://openalex.org/W6693341220","https://openalex.org/W6697214482"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W3210945214"],"abstract_inverted_index":{"Traditional":[0],"remote":[1,24,39,175],"sensing":[2,25,40,176],"image":[3,54,79,136],"retrieval":[4,68,80,127,144,168,191],"(RSIR)":[5],"methods":[6,192],"are":[7],"generally":[8],"based":[9,89],"on":[10,90,173],"images":[11,26,41,126],"from":[12,48,52],"a":[13,85,117,134,147],"specific":[14],"single":[15],"source.":[16],"As":[17],"different":[18,43,49],"sources":[19],"and":[20,45,62,66,112,128,138],"huge":[21],"volumes":[22],"of":[23,37,58,70,116,140],"have":[27],"been":[28],"easily":[29],"available":[30],"nowadays,":[31],"RSIR":[32,98],"is":[33,93,113,153,196],"facing":[34],"the":[35,167],"challenge":[36],"retrieving":[38],"with":[42],"spectral":[44],"spatial":[46],"information":[47],"sources.":[50],"Benefited":[51],"compelling":[53],"feature":[55],"extraction":[56],"ability":[57,69],"deep":[59,72,86,102,120,130],"neural":[60],"networks":[61,74],"efficient":[63],"computing":[64],"power":[65],"effective":[67],"hashing,":[71],"hashing":[73,87,103,121,131],"has":[75],"become":[76],"prevalent":[77],"for":[78,95,123,133,150],"researches.":[81],"In":[82],"this":[83],"paper,":[84],"network":[88],"split":[91],"channels":[92,109],"proposed":[94,181],"hybrid":[96,118,189],"source":[97,119,125,190],"called":[99,155],"split-channels":[100],"triplet":[101],"networks(SCTDHNs).":[104],"It":[105],"takes":[106],"skillfully":[107],"splitting":[108],"as":[110,193,195],"input,":[111],"mainly":[114],"composed":[115],"subnetwork":[122],"cross":[124],"single-source":[129],"sub-network":[132],"multi-spectral":[135],"retrieval,":[137],"each":[139],"them":[141],"achieves":[142],"high":[143],"performance.":[145,169],"Furthermore,":[146],"novel":[148],"trick":[149],"loss":[151],"function":[152],"proposed,":[154],"increased":[156],"intervals":[157],"between":[158],"dissimilar":[159],"pairs":[160],"during":[161],"training":[162],"stage":[163],"that":[164,180],"dramatically":[165],"improves":[166],"Extensive":[170],"experiments":[171],"implement":[172],"dual-source":[174],"data":[177],"set":[178],"demonstrate":[179],"method":[182],"yields":[183],"better":[184],"performance":[185],"than":[186],"existing":[187],"state-of-art":[188],"far":[194],"known.":[197]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}