{"id":"https://openalex.org/W3130093756","doi":"https://doi.org/10.1109/igarss39084.2020.9324150","title":"Small Object Change Detection Based on Multitask Siamese Network","display_name":"Small Object Change Detection Based on Multitask Siamese Network","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3130093756","doi":"https://doi.org/10.1109/igarss39084.2020.9324150","mag":"3130093756"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9324150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","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/A5074292246","display_name":"Shreya Sharma","orcid":"https://orcid.org/0000-0001-7547-8867"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shreya Sharma","raw_affiliation_strings":["Data Science Research Laboratories, NEC Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Laboratories, NEC Corporation","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080963318","display_name":"Eiji Kaneko","orcid":"https://orcid.org/0000-0003-1840-5551"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Eiji Kaneko","raw_affiliation_strings":["Data Science Research Laboratories, NEC Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Laboratories, NEC Corporation","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066517717","display_name":"Masato Toda","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masato Toda","raw_affiliation_strings":["Data Science Research Laboratories, NEC Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Laboratories, NEC Corporation","institution_ids":["https://openalex.org/I118347220"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.3222252,"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":"300","last_page":"303"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.992900013923645,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.8134927749633789},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7723841667175293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7195539474487305},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6477166414260864},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6221757531166077},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5449160933494568},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5286726951599121},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5115383863449097},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5091609358787537},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5021910667419434},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.45862334966659546},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.41214632987976074},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41204720735549927},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.27446722984313965},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07116499543190002}],"concepts":[{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.8134927749633789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7723841667175293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7195539474487305},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6477166414260864},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6221757531166077},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5449160933494568},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5286726951599121},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5115383863449097},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5091609358787537},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5021910667419434},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.45862334966659546},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.41214632987976074},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41204720735549927},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27446722984313965},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07116499543190002},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9324150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2140023211","https://openalex.org/W2144552105","https://openalex.org/W2615543373","https://openalex.org/W2751993439","https://openalex.org/W6637373629"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W4255837520","https://openalex.org/W3135697610","https://openalex.org/W2376528221","https://openalex.org/W196800607","https://openalex.org/W2359428812","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,82],"small":[4,73],"object,":[5],"represented":[6],"by":[7,57,106,126],"approximately":[8],"ten":[9],"pixels":[10],"in":[11],"an":[12],"image,":[13],"change":[14,32,55,102,123],"detection":[15,33,56],"method":[16,80,129,136],"based":[17,113],"on":[18,114],"multitask":[19],"Siamese":[20,118],"network":[21,69],"for":[22,81],"multitemporal":[23],"SAR":[24],"images.":[25,94],"In":[26],"our":[27],"proposed":[28,79,128],"method,":[29],"not":[30],"only":[31],"task":[34,39,47],"but":[35],"also":[36],"object":[37,74],"classification":[38,46,139],"is":[40,48,104,124],"introduced":[41],"to":[42,50,64],"the":[43,52,68,71,78,99,127,135,138],"network.":[44,119],"The":[45],"expected":[49],"enhance":[51],"performance":[53],"of":[54,61,67,85,101],"providing":[58],"semantic":[59],"information":[60],"changes":[62],"and":[63,117],"focus":[65],"attention":[66],"towards":[70],"target":[72],"class.":[75],"We":[76],"tested":[77],"real-world":[83],"application":[84],"car":[86],"parking":[87],"lot":[88],"monitoring":[89],"with":[90,130],"1-meter":[91],"resolution":[92],"TerraSAR-X":[93],"Experimental":[95],"results":[96],"show":[97],"that":[98],"f-measure":[100],"class":[103],"improved":[105],"more":[107],"than":[108],"7%":[109],"over":[110,134],"conventional":[111],"methods":[112],"post-classification,":[115],"PCA+K-means":[116],"Furthermore,":[120],"car-to-car":[121],"type":[122],"detected":[125],"25%":[131],"higher":[132],"accuracy":[133],"without":[137],"task.":[140]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
