{"id":"https://openalex.org/W2901223228","doi":"https://doi.org/10.1109/igarss.2018.8518138","title":"Innovative Multi Pcnn Based Network for Green Area Monitoring - Identification and Description of Nearly Indistinguishable Areas - In Hyperspectral Satellite Images","display_name":"Innovative Multi Pcnn Based Network for Green Area Monitoring - Identification and Description of Nearly Indistinguishable Areas - In Hyperspectral Satellite Images","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901223228","doi":"https://doi.org/10.1109/igarss.2018.8518138","mag":"2901223228"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518138","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518138","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 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/A5047089128","display_name":"Serban Carata","orcid":"https://orcid.org/0000-0003-4995-9805"},"institutions":[{"id":"https://openalex.org/I4210142834","display_name":"Institute of Space Science - INFLPR Subsidiary","ror":"https://ror.org/054a6wv56","country_code":"RO","type":"facility","lineage":["https://openalex.org/I4210142834"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Serban- Vasile Carata","raw_affiliation_strings":["Institute of Space Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Space Science","institution_ids":["https://openalex.org/I4210142834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026839903","display_name":"Mihai Gabriel Constantin","orcid":"https://orcid.org/0000-0002-2312-6672"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Mihai-Gabriel Constantin","raw_affiliation_strings":["University Politehnica of Bucharest"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008453296","display_name":"V. Ghenescu","orcid":"https://orcid.org/0000-0002-8110-0403"},"institutions":[{"id":"https://openalex.org/I4210142834","display_name":"Institute of Space Science - INFLPR Subsidiary","ror":"https://ror.org/054a6wv56","country_code":"RO","type":"facility","lineage":["https://openalex.org/I4210142834"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Veta Ghenescu","raw_affiliation_strings":["Institute of Space Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Space Science","institution_ids":["https://openalex.org/I4210142834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088264914","display_name":"Mihai Chindea","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mihai Chindea","raw_affiliation_strings":["UTI Grup"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UTI Grup","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049395340","display_name":"Marian Ghenescu","orcid":"https://orcid.org/0009-0007-2319-7028"},"institutions":[{"id":"https://openalex.org/I4210142834","display_name":"Institute of Space Science - INFLPR Subsidiary","ror":"https://ror.org/054a6wv56","country_code":"RO","type":"facility","lineage":["https://openalex.org/I4210142834"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Marian Ghenescu","raw_affiliation_strings":["Institute of Space Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Space Science","institution_ids":["https://openalex.org/I4210142834"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"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":0.1885451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"8","issue":null,"first_page":"2639","last_page":"2642"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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":0.9994999766349792,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9936000108718872,"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"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7217891812324524},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6561278104782104},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6362047791481018},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.568272590637207},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5263912677764893},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5220596790313721},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.4994187355041504},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.49896883964538574},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4815673828125},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.44904083013534546},{"id":"https://openalex.org/keywords/footprint","display_name":"Footprint","score":0.4235174059867859},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.36457139253616333},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34669142961502075},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2410888671875},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07621529698371887}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7217891812324524},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6561278104782104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6362047791481018},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.568272590637207},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5263912677764893},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5220596790313721},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.4994187355041504},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.49896883964538574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4815673828125},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44904083013534546},{"id":"https://openalex.org/C132943942","wikidata":"https://www.wikidata.org/wiki/Q2562511","display_name":"Footprint","level":2,"score":0.4235174059867859},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.36457139253616333},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34669142961502075},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2410888671875},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07621529698371887},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8518138","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518138","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1637508839","https://openalex.org/W1979061792","https://openalex.org/W1982147649","https://openalex.org/W2032843526","https://openalex.org/W2060426168","https://openalex.org/W2094618681","https://openalex.org/W2098281478","https://openalex.org/W2150729352","https://openalex.org/W2161776042","https://openalex.org/W2276327097","https://openalex.org/W2548535335","https://openalex.org/W2768149277","https://openalex.org/W2963037989","https://openalex.org/W4239510810"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2901421464","https://openalex.org/W2932657337"],"abstract_inverted_index":{"The":[0,19,65,74,101],"paper":[1],"presents":[2],"an":[3],"original":[4],"neural":[5],"network":[6],"approach":[7],"for":[8,55],"region":[9],"of":[10,25,34,97,121],"interest":[11],"detection":[12],"and":[13,113],"classification":[14],"in":[15,48,88,127],"multi-spectral":[16],"satellite":[17],"images.":[18],"proposed":[20],"method":[21],"uses":[22],"a":[23,41,56,71,89],"sequence":[24],"Pulse":[26],"Coupled":[27],"Neural":[28],"Networks":[29],"that":[30,61,81,91,116],"identifies":[31],"plausible":[32],"regions":[33,37,80],"interest.":[35],"These":[36],"are":[38,68,82],"passed":[39],"to":[40,50,78],"dimension":[42],"reduction":[43],"algorithm,":[44],"Principle":[45],"Component":[46],"Analysis,":[47],"order":[49],"generate":[51],"the":[52,63,110,122,128],"input":[53],"data":[54],"Support":[57],"Vector":[58],"Machine":[59],"classifier,":[60],"validates":[62],"data.":[64],"algorithm's":[66],"parameters":[67],"optimized":[69],"using":[70],"Genetic":[72],"Algorithm.":[73],"algorithm":[75,102],"is":[76],"designed":[77],"distinguish":[79],"extremely":[83],"similar,":[84],"such":[85],"as":[86,125],"parks":[87],"city":[90],"has":[92,103],"entire":[93],"districts":[94],"made":[95],"up":[96],"houses":[98],"with":[99],"yards.":[100],"been":[104],"tested":[105],"on":[106],"images":[107],"provided":[108],"by":[109],"Sentinel-2":[111],"satellite,":[112],"it":[114,117],"proved":[115],"can":[118],"recall":[119],"76.85%":[120],"pixels":[123],"marked":[124],"park":[126],"ground":[129],"truth":[130],"data,":[131],"which":[132],"was":[133],"obtained":[134],"from":[135],"Open":[136],"Street":[137],"Map.":[138]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
