{"id":"https://openalex.org/W2794295145","doi":"https://doi.org/10.3390/rs10030457","title":"An Object-Based Image Analysis Method for Enhancing Classification of Land Covers Using Fully Convolutional Networks and Multi-View Images of Small Unmanned Aerial System","display_name":"An Object-Based Image Analysis Method for Enhancing Classification of Land Covers Using Fully Convolutional Networks and Multi-View Images of Small Unmanned Aerial System","publication_year":2018,"publication_date":"2018-03-14","ids":{"openalex":"https://openalex.org/W2794295145","doi":"https://doi.org/10.3390/rs10030457","mag":"2794295145"},"language":"en","primary_location":{"id":"doi:10.3390/rs10030457","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10030457","pdf_url":"https://www.mdpi.com/2072-4292/10/3/457/pdf?version=1521017648","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/10/3/457/pdf?version=1521017648","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047430579","display_name":"Tao Liu","orcid":"https://orcid.org/0000-0001-5917-8303"},"institutions":[{"id":"https://openalex.org/I2801014300","display_name":"Florida Gulf Coast University","ror":"https://ror.org/05tc5bm31","country_code":"US","type":"education","lineage":["https://openalex.org/I2801014300"]},{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tao Liu","raw_affiliation_strings":["Gulf Coast Research Center, University of Florida, Plant City, FL 33563, USA","School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA"],"affiliations":[{"raw_affiliation_string":"Gulf Coast Research Center, University of Florida, Plant City, FL 33563, USA","institution_ids":["https://openalex.org/I2801014300","https://openalex.org/I33213144"]},{"raw_affiliation_string":"School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037840997","display_name":"Amr Abd\u2010Elrahman","orcid":"https://orcid.org/0000-0002-6182-4017"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]},{"id":"https://openalex.org/I2801014300","display_name":"Florida Gulf Coast University","ror":"https://ror.org/05tc5bm31","country_code":"US","type":"education","lineage":["https://openalex.org/I2801014300"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amr Abd-Elrahman","raw_affiliation_strings":["Gulf Coast Research Center, University of Florida, Plant City, FL 33563, USA","School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA"],"affiliations":[{"raw_affiliation_string":"Gulf Coast Research Center, University of Florida, Plant City, FL 33563, USA","institution_ids":["https://openalex.org/I2801014300","https://openalex.org/I33213144"]},{"raw_affiliation_string":"School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047430579"],"corresponding_institution_ids":["https://openalex.org/I2801014300","https://openalex.org/I33213144"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.937,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.95435516,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"10","issue":"3","first_page":"457","last_page":"457"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"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":0.9995999932289124,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9994000196456909,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9962000250816345,"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/computer-science","display_name":"Computer science","score":0.7792221307754517},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7155278325080872},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6973124742507935},{"id":"https://openalex.org/keywords/orthophoto","display_name":"Orthophoto","score":0.6514365077018738},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6133862733840942},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5608704686164856},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5453734397888184},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.544990599155426},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.42222753167152405},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32461875677108765},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24190768599510193}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7792221307754517},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7155278325080872},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6973124742507935},{"id":"https://openalex.org/C82789328","wikidata":"https://www.wikidata.org/wiki/Q922585","display_name":"Orthophoto","level":2,"score":0.6514365077018738},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6133862733840942},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5608704686164856},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5453734397888184},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.544990599155426},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.42222753167152405},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32461875677108765},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24190768599510193},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs10030457","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10030457","pdf_url":"https://www.mdpi.com/2072-4292/10/3/457/pdf?version=1521017648","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c3dc919583d14fb58449b41514b35c45","is_oa":true,"landing_page_url":"https://doaj.org/article/c3dc919583d14fb58449b41514b35c45","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 10, Iss 3, p 457 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/10/3/457/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs10030457","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 10; Issue 3; Pages: 457","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs10030457","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10030457","pdf_url":"https://www.mdpi.com/2072-4292/10/3/457/pdf?version=1521017648","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2794295145.pdf","grobid_xml":"https://content.openalex.org/works/W2794295145.grobid-xml"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1482862163","https://openalex.org/W1553083334","https://openalex.org/W1560724230","https://openalex.org/W1585377561","https://openalex.org/W1665214252","https://openalex.org/W1903029394","https://openalex.org/W1904365287","https://openalex.org/W1966580635","https://openalex.org/W1972023946","https://openalex.org/W1982437503","https://openalex.org/W1984792953","https://openalex.org/W1998943389","https://openalex.org/W2014337138","https://openalex.org/W2035791899","https://openalex.org/W2061356545","https://openalex.org/W2075729651","https://openalex.org/W2078478672","https://openalex.org/W2101051003","https://openalex.org/W2115080712","https://openalex.org/W2126598020","https://openalex.org/W2129940092","https://openalex.org/W2136922672","https://openalex.org/W2150986124","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2165698076","https://openalex.org/W2172000360","https://openalex.org/W2186079019","https://openalex.org/W2189288378","https://openalex.org/W2196197460","https://openalex.org/W2224174650","https://openalex.org/W2257979135","https://openalex.org/W2261059368","https://openalex.org/W2267317359","https://openalex.org/W2331814172","https://openalex.org/W2344005843","https://openalex.org/W2480140235","https://openalex.org/W2480562445","https://openalex.org/W2488187315","https://openalex.org/W2522698497","https://openalex.org/W2536614103","https://openalex.org/W2573123177","https://openalex.org/W2586954532","https://openalex.org/W2591213449","https://openalex.org/W2593771152","https://openalex.org/W2599585299","https://openalex.org/W2600701715","https://openalex.org/W2617645388","https://openalex.org/W2623490820","https://openalex.org/W2648242067","https://openalex.org/W2740982025","https://openalex.org/W2752983793","https://openalex.org/W2766447205","https://openalex.org/W2776305546","https://openalex.org/W2782438771","https://openalex.org/W2782934949","https://openalex.org/W2793091350","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W2963578416","https://openalex.org/W3102779874","https://openalex.org/W4239510810","https://openalex.org/W6658967404","https://openalex.org/W6687010205"],"related_works":["https://openalex.org/W2952813363","https://openalex.org/W2911497689","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W2770149305","https://openalex.org/W2972076240","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W2964843961","https://openalex.org/W3010730661"],"abstract_inverted_index":{"Fully":[0],"Convolutional":[1,22],"Networks":[2],"(FCN)":[3],"has":[4,53],"shown":[5],"better":[6,181,223],"performance":[7],"than":[8,183,225],"other":[9,111,132,227],"classifiers":[10],"like":[11],"Random":[12],"Forest":[13],"(RF),":[14],"Support":[15],"Vector":[16],"Machine":[17],"(SVM)":[18],"and":[19,69,105,112,117],"patch-based":[20],"Deep":[21],"Neural":[23],"Network":[24],"(DCNN),":[25],"for":[26,36,48,57,79],"object-based":[27,101,148],"classification":[28,66,102,149,185],"using":[29,67,103,207,231],"orthoimage":[30,95,154,232],"only":[31],"in":[32],"previous":[33],"studies;":[34],"however,":[35],"further":[37],"improving":[38],"deep":[39],"learning":[40],"algorithm":[41],"performance,":[42],"multi-view":[43,70,91,100,147,164,234],"data":[44,50,71,155],"should":[45],"be":[46],"considered":[47],"training":[49,92,96,165],"enrichment,":[51],"which":[52],"not":[54,124],"been":[55],"investigated":[56],"FCN.":[58],"The":[59,120],"present":[60],"study":[61,84],"developed":[62],"a":[63],"novel":[64],"OBIA":[65],"FCN":[68,146,174,184,213,220],"extracted":[72],"from":[73,94,194],"small":[74],"Unmanned":[75],"Aerial":[76],"System":[77],"(UAS)":[78],"mapping":[80],"landcovers.":[81],"Specifically,":[82],"this":[83],"proposed":[85],"three":[86,143],"methods":[87,197],"to":[88,98],"automatically":[89],"generate":[90],"samples":[93,166,178],"datasets":[97],"conduct":[99],"FCN,":[104],"compared":[106],"their":[107,151],"performances":[108],"with":[109,114,169,176,214],"each":[110],"also":[113,160],"RF,":[115,215],"SVM,":[116,216],"DCNN":[118,217],"classifiers.":[119],"first":[121],"method":[122],"does":[123],"consider":[125],"the":[126,131,142,158,195,226],"object":[127,135,172,199],"surrounding":[128,200],"information,":[129,201],"while":[130],"two":[133,196,208],"utilized":[134],"context":[136,188],"information.":[137,189],"We":[138],"demonstrated":[139],"that":[140,162,219],"all":[141],"versions":[144],"of":[145,171,230],"outperformed":[150],"counterparts":[152],"utilizing":[153,198],"only.":[156],"Furthermore,":[157],"results":[159],"showed":[161],"when":[163],"were":[167,192],"prepared":[168],"consideration":[170],"surroundings,":[173],"trained":[175,186],"these":[177],"gave":[179],"much":[180],"accuracy":[182,224],"without":[187],"Similar":[190],"accuracies":[191],"achieved":[193],"although":[202],"sample":[203],"preparation":[204],"was":[205],"conducted":[206],"different":[209],"ways.":[210],"When":[211],"comparing":[212],"implies":[218],"generally":[221],"produced":[222],"classifiers,":[228],"regardless":[229],"or":[233],"data.":[235]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}