{"id":"https://openalex.org/W2398200363","doi":"https://doi.org/10.1007/978-3-319-12568-8_124","title":"Data Fusion Approach for Employing Multiple Classifiers to Improve Lake Shoreline Analysis","display_name":"Data Fusion Approach for Employing Multiple Classifiers to Improve Lake Shoreline Analysis","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2398200363","doi":"https://doi.org/10.1007/978-3-319-12568-8_124","mag":"2398200363"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-319-12568-8_124","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-319-12568-8_124","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-319-12568-8_124.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/978-3-319-12568-8_124.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055970775","display_name":"Alejandra A. L\u00f3pez-Caloca","orcid":"https://orcid.org/0000-0002-8426-1050"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Alejandra A. L\u00f3pez-Caloca","raw_affiliation_strings":["Centro de Investigaci\u00f3n en Geograf\u00eda y Geom\u00e1tica, Mexico, D.F., Mexico"],"affiliations":[{"raw_affiliation_string":"Centro de Investigaci\u00f3n en Geograf\u00eda y Geom\u00e1tica, Mexico, D.F., Mexico","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5055970775"],"corresponding_institution_ids":[],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":0.3656,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.77698076,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1022","last_page":"1029"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10577","display_name":"Hydrology and Sediment Transport Processes","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.796298623085022},{"id":"https://openalex.org/keywords/watershed","display_name":"Watershed","score":0.6638904809951782},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6357338428497314},{"id":"https://openalex.org/keywords/shore","display_name":"Shore","score":0.6162229180335999},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.60638827085495},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5173355937004089},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5114278197288513},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5112357139587402},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4891531765460968},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.48425957560539246},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46547386050224304},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.44416284561157227},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40875792503356934},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3447118401527405},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10804438591003418}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.796298623085022},{"id":"https://openalex.org/C150547873","wikidata":"https://www.wikidata.org/wiki/Q947851","display_name":"Watershed","level":2,"score":0.6638904809951782},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6357338428497314},{"id":"https://openalex.org/C152382732","wikidata":"https://www.wikidata.org/wiki/Q468756","display_name":"Shore","level":2,"score":0.6162229180335999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.60638827085495},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5173355937004089},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5114278197288513},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5112357139587402},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4891531765460968},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.48425957560539246},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46547386050224304},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.44416284561157227},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40875792503356934},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3447118401527405},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10804438591003418},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-319-12568-8_124","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-319-12568-8_124","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-319-12568-8_124.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-319-12568-8_124","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-319-12568-8_124","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-319-12568-8_124.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2398200363.pdf","grobid_xml":"https://content.openalex.org/works/W2398200363.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1976044762","https://openalex.org/W1990763929","https://openalex.org/W1992018127","https://openalex.org/W1993795766","https://openalex.org/W2056356839","https://openalex.org/W2077509829","https://openalex.org/W2091894170","https://openalex.org/W2101678239","https://openalex.org/W2117308911","https://openalex.org/W2123477536","https://openalex.org/W2133059825","https://openalex.org/W2145087958","https://openalex.org/W2149730711","https://openalex.org/W2154985549","https://openalex.org/W2309693750","https://openalex.org/W2363608402","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2031175860","https://openalex.org/W2152662039","https://openalex.org/W2726747157","https://openalex.org/W2010131506","https://openalex.org/W2392133813","https://openalex.org/W2145797872"],"abstract_inverted_index":{"Remote":[0],"sensing":[1],"images":[2],"have":[3,13],"been":[4,85],"widely":[5],"employed":[6],"to":[7,16,66,87,94],"analyze":[8],"bodies":[9],"of":[10,23,78,113],"water":[11,39],"and":[12,54],"become":[14],"essential":[15],"studying":[17],"their":[18],"dynamics.":[19],"While":[20],"the":[21,27,33,73,105,111],"use":[22,77],"indices":[24],"based":[25,51],"on":[26,52],"threshold":[28],"segmentation":[29,44,74,82],"technique":[30],"is":[31,50,92],"preferred,":[32],"search":[34],"for":[35],"methods":[36],"that":[37,69,104],"define":[38],"edge":[40],"contour":[41],"continues.":[42],"The":[43,76],"algorithm":[45],"introduced":[46],"in":[47],"this":[48],"study":[49],"Mean-Shift":[53],"Watershed":[55],"methods.":[56],"We":[57],"propose":[58],"a":[59,96],"fusion":[60],"classifier":[61],"strategy":[62],"which":[63],"allows":[64],"us":[65],"obtain":[67],"results":[68,102],"are":[70],"consistent":[71],"with":[72],"process.":[75],"two":[79],"or":[80],"more":[81],"processes":[83],"has":[84],"shown":[86],"improve":[88,110],"pattern":[89],"recognition.":[90],"It":[91],"important":[93],"implement":[95],"good":[97],"data":[98],"integration":[99],"scheme.":[100],"Preliminary":[101],"suggest":[103],"approach":[106],"reported":[107],"herein":[108],"can":[109],"definition":[112],"lake":[114],"shorelines.":[115]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}