{"id":"https://openalex.org/W2100083764","doi":"https://doi.org/10.1109/lgrs.2009.2014083","title":"Image Mining Using Directional Spatial Constraints","display_name":"Image Mining Using Directional Spatial Constraints","publication_year":2009,"publication_date":"2009-03-19","ids":{"openalex":"https://openalex.org/W2100083764","doi":"https://doi.org/10.1109/lgrs.2009.2014083","mag":"2100083764"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2009.2014083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2009.2014083","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5003826893","display_name":"Selim Aksoy","orcid":"https://orcid.org/0000-0003-4185-0565"},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Selim Aksoy","raw_affiliation_strings":["Department of Computer Engineering, Bilkent University, Ankara, Turkey","Department of Computer Engineering Bilkent University  Ankara Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Bilkent University, Ankara, Turkey","institution_ids":["https://openalex.org/I168864056"]},{"raw_affiliation_string":"Department of Computer Engineering Bilkent University  Ankara Turkey","institution_ids":["https://openalex.org/I168864056"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051499142","display_name":"Ramazan G\u00f6kberk Cinbi\u015f","orcid":"https://orcid.org/0000-0003-0962-7101"},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"R. G\u00d6kberk Cinbis","raw_affiliation_strings":["Department of Computer Engineering, Bilkent University, Ankara, Turkey","Department of Computer Engineering Bilkent University  Ankara Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Bilkent University, Ankara, Turkey","institution_ids":["https://openalex.org/I168864056"]},{"raw_affiliation_string":"Department of Computer Engineering Bilkent University  Ankara Turkey","institution_ids":["https://openalex.org/I168864056"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I168864056"],"apc_list":null,"apc_paid":null,"fwci":3.5499,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.9280132,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"7","issue":"1","first_page":"33","last_page":"37"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9977999925613403,"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":0.9943000078201294,"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":0.7883138656616211},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.7193949818611145},{"id":"https://openalex.org/keywords/spatial-relation","display_name":"Spatial relation","score":0.6346310973167419},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.6135976910591125},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.5200604796409607},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5150746703147888},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5052252411842346},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.488252192735672},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.47936731576919556},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.46343857049942017},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43049195408821106},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.42915529012680054},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.416332870721817},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3940427005290985},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3624476194381714},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.22340700030326843},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10554596781730652},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09769687056541443}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7883138656616211},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.7193949818611145},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.6346310973167419},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.6135976910591125},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5200604796409607},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5150746703147888},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5052252411842346},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.488252192735672},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.47936731576919556},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.46343857049942017},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43049195408821106},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.42915529012680054},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.416332870721817},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3940427005290985},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3624476194381714},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.22340700030326843},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10554596781730652},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09769687056541443},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/lgrs.2009.2014083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2009.2014083","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.712.9645","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.712.9645","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.bilkent.edu.tr/%7Esaksoy/papers/grsl_spatial_mining.pdf","raw_type":"text"},{"id":"pmh:oai:https://open.metu.edu.tr:11511/38429","is_oa":false,"landing_page_url":"https://hdl.handle.net/11511/38429","pdf_url":null,"source":{"id":"https://openalex.org/S4306402495","display_name":"OpenMETU (Middle East Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I201799495","host_organization_name":"Middle East Technical University","host_organization_lineage":["https://openalex.org/I201799495"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"},{"id":"pmh:oai:repository.bilkent.edu.tr:11693/11710","is_oa":false,"landing_page_url":"http://hdl.handle.net/11693/11710","pdf_url":null,"source":{"id":"https://openalex.org/S4306400079","display_name":"Bilkent University Institutional Repository (Bilkent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I168864056","host_organization_name":"Bilkent University","host_organization_lineage":["https://openalex.org/I168864056"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"Article"},{"id":"pmh:oai:repository.bilkent.edu.tr:11693/22482","is_oa":false,"landing_page_url":"http://hdl.handle.net/11693/22482","pdf_url":null,"source":{"id":"https://openalex.org/S4306400079","display_name":"Bilkent University Institutional Repository (Bilkent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I168864056","host_organization_name":"Bilkent University","host_organization_lineage":["https://openalex.org/I168864056"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6399999856948853,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322626","display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu","ror":"https://ror.org/04w9kkr77"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1497995627","https://openalex.org/W2098738957","https://openalex.org/W2149140633","https://openalex.org/W2156575832","https://openalex.org/W2161298738","https://openalex.org/W2168481210","https://openalex.org/W2501746074"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W4389195459","https://openalex.org/W2520082489","https://openalex.org/W2925311845","https://openalex.org/W2362913948","https://openalex.org/W2116266067","https://openalex.org/W2364189591","https://openalex.org/W2028237718"],"abstract_inverted_index":{"Spatial":[0],"information":[1,33,65],"plays":[2],"a":[3,21,48,54],"fundamental":[4],"role":[5],"in":[6,127,133],"building":[7],"high-level":[8],"content":[9],"models":[10],"for":[11,23,34,76],"supporting":[12],"analysts'":[13],"interpretations":[14],"and":[15,30,37,121,136],"automating":[16],"geospatial":[17],"intelligence.":[18],"We":[19],"describe":[20],"framework":[22,126],"modeling":[24],"directional":[25,87],"spatial":[26,55,74,90,107],"relationships":[27,88,108],"among":[28],"objects":[29,102],"using":[31,86,114],"this":[32,64],"contextual":[35,77],"classification":[36,135],"retrieval.":[38],"The":[39,79],"proposed":[40,125],"model":[41,80],"first":[42],"identifies":[43],"image":[44,128],"areas":[45],"that":[46],"have":[47],"high":[49],"degree":[50],"of":[51,53,100,123],"satisfaction":[52],"relation":[56],"with":[57,130],"respect":[58],"to":[59,92,109],"several":[60],"reference":[61],"objects.":[62,111],"Then,":[63],"is":[66],"incorporated":[67],"into":[68],"the":[69,98,119,124],"Bayesian":[70],"decision":[71],"rule":[72],"as":[73,89,103,105],"priors":[75],"classification.":[78],"also":[81],"supports":[82],"dynamic":[83],"queries":[84],"by":[85],"constraints":[91],"enable":[93],"object":[94],"detection":[95],"based":[96],"on":[97],"properties":[99],"individual":[101],"well":[104],"their":[106],"other":[110],"Comparative":[112],"experiments":[113],"high-resolution":[115],"satellite":[116],"imagery":[117],"illustrate":[118],"flexibility":[120],"effectiveness":[122],"mining":[129],"significant":[131],"improvements":[132],"both":[134],"retrieval":[137],"performance.":[138]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":6}],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2025-10-10T00:00:00"}
