{"id":"https://openalex.org/W1992129756","doi":"https://doi.org/10.1145/2683483.2683525","title":"A novel graph matching based approach for land-cover classification of multi-temporal images","display_name":"A novel graph matching based approach for land-cover classification of multi-temporal images","publication_year":2014,"publication_date":"2014-12-14","ids":{"openalex":"https://openalex.org/W1992129756","doi":"https://doi.org/10.1145/2683483.2683525","mag":"1992129756"},"language":"en","primary_location":{"id":"doi:10.1145/2683483.2683525","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2683483.2683525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing","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/A5020786167","display_name":"Biplab Banerjee","orcid":"https://orcid.org/0000-0001-8371-8138"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Biplab Banerjee","raw_affiliation_strings":["CSRE, IIT Bombay","CSRE, IIT, Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CSRE, IIT Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"CSRE, IIT, Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114063078","display_name":"B. Krishna Mohan","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"B. Krishna Mohan","raw_affiliation_strings":["CSRE, IIT Bombay","CSRE, IIT, Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CSRE, IIT Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"CSRE, IIT, Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016405213","display_name":"Subhasis Chaudhuri","orcid":"https://orcid.org/0000-0002-1680-0016"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subhasis Chaudhuri","raw_affiliation_strings":["EE, IIT Bombay","[EE, IIT Bombay]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EE, IIT Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"[EE, IIT Bombay]","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057547054","display_name":"Avik Bhattacharya","orcid":"https://orcid.org/0000-0001-6720-6108"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Avik Bhattacharya","raw_affiliation_strings":["CSRE, IIT Bombay","CSRE, IIT, Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CSRE, IIT Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"CSRE, IIT, Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jyotirmoy Mohanty","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jyotirmoy Mohanty","raw_affiliation_strings":["CSRE, IIT Bombay","CSRE, IIT, Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CSRE, IIT Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"CSRE, IIT, Bombay","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5897,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.65682973,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12292","display_name":"Graph Theory and Algorithms","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6491754055023193},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6394025683403015},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5548356175422668},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5355814099311829},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5169650912284851},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.5021333694458008},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.49847960472106934},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.49226871132850647},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4639790654182434},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44958755373954773},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4469284117221832},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.42750293016433716},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.41584280133247375},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37126240134239197},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.3681219220161438},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2780463695526123},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08929362893104553}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6491754055023193},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6394025683403015},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5548356175422668},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5355814099311829},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5169650912284851},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.5021333694458008},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.49847960472106934},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.49226871132850647},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4639790654182434},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44958755373954773},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4469284117221832},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.42750293016433716},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.41584280133247375},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37126240134239197},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.3681219220161438},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2780463695526123},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08929362893104553},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.0},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2683483.2683525","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2683483.2683525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.41999998688697815}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322275","display_name":"Universit\u00e0 degli Studi di Trento","ror":"https://ror.org/05trd4x28"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1506806321","https://openalex.org/W1601795611","https://openalex.org/W1996118086","https://openalex.org/W2019239972","https://openalex.org/W2024886312","https://openalex.org/W2054407194","https://openalex.org/W2108290454","https://openalex.org/W2109294083","https://openalex.org/W2129932701","https://openalex.org/W2136236240","https://openalex.org/W2137900926","https://openalex.org/W2149498498","https://openalex.org/W2154558852","https://openalex.org/W2159570078","https://openalex.org/W6679518175"],"related_works":["https://openalex.org/W1978153144","https://openalex.org/W102848802","https://openalex.org/W1976188970","https://openalex.org/W2982058819","https://openalex.org/W2130734797","https://openalex.org/W3176361882","https://openalex.org/W2025556230","https://openalex.org/W2889559465","https://openalex.org/W2150061385","https://openalex.org/W2990541822"],"abstract_inverted_index":{"We":[0],"address":[1],"the":[2,26,40,48,54,63,83,86,93,97,116,120,130,138,158,173,177,181,184,195,196,199],"problem":[3],"of":[4,9,22,47,89,96,119,180,198],"automatic":[5],"land-cover":[6,90],"map":[7,74],"updating":[8],"multi-temporal":[10],"and":[11,176],"multi-spectral":[12,192],"remotely":[13],"sensed":[14],"images":[15,23,84],"in":[16,137,183],"this":[17],"paper.":[18],"Given":[19,128],"a":[20,107,142,149],"pair":[21],"acquired":[24],"on":[25,191],"same":[27,87],"geographical":[28],"area":[29],"at":[30],"two":[31],"distinct":[32],"time":[33],"instants,":[34],"it":[35],"is":[36,51,60,75,78,112,125,166],"assumed":[37,80],"here":[38],"that":[39,81,129],"training":[41],"data":[42,123],"are":[43],"available":[44],"for":[45,69],"one":[46],"acquisitions,":[49],"which":[50,70,124,141],"known":[52],"as":[53],"source":[55],"domain":[56,67,122,186],"image.":[57,187],"The":[58],"task":[59],"to":[61,114,146,169],"classify":[62],"other":[64],"image":[65],"(target":[66],"image)":[68],"no":[71],"reliable":[72],"reference":[73],"available.":[76],"It":[77],"further":[79,170],"both":[82],"share":[85],"set":[88],"classes":[91,98,134,182],"though":[92],"statistical":[94],"properties":[95],"may":[99,135],"change":[100],"considerably":[101],"over":[102],"time.":[103],"Under":[104],"these":[105],"assumptions,":[106],"novel":[108],"graph":[109],"matching":[110],"technique":[111],"proposed":[113,200],"approximate":[115],"class":[117],"labels":[118],"target":[121,185],"initially":[126],"clustered.":[127],"samples":[131],"from":[132],"different":[133],"overlap":[136],"spectral":[139],"domain,":[140],"clustering":[143],"algorithm":[144],"fails":[145],"detect":[147],"properly,":[148],"partially":[150],"supervised":[151],"Maximum":[152],"Likelihood":[153],"(ML)":[154],"classifier":[155],"coupled":[156],"with":[157],"Expectation":[159],"Maximization":[160],"(EM)":[161],"based":[162],"parameter":[163],"re-training":[164],"scheme":[165],"used":[167],"iteratively":[168],"jointly":[171],"update":[172],"class-conditional":[174],"densities":[175],"prior":[178],"probabilities":[179],"Experimental":[188],"results":[189],"obtained":[190],"datasets":[193],"confirm":[194],"effectiveness":[197],"method.":[201]},"counts_by_year":[{"year":2016,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}