{"id":"https://openalex.org/W2411277885","doi":"https://doi.org/10.1109/iwssip.2016.7502739","title":"Improved image classification by proper patch size selection: TerraSAR-X vs. Sentinel-1A","display_name":"Improved image classification by proper patch size selection: TerraSAR-X vs. Sentinel-1A","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2411277885","doi":"https://doi.org/10.1109/iwssip.2016.7502739","mag":"2411277885"},"language":"en","primary_location":{"id":"doi:10.1109/iwssip.2016.7502739","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwssip.2016.7502739","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Systems, Signals and Image Processing (IWSSIP)","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/A5032852455","display_name":"Corneliu Octavian Dumitru","orcid":"https://orcid.org/0000-0001-5707-1799"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Corneliu Octavian Dumitru","raw_affiliation_strings":["Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany"],"affiliations":[{"raw_affiliation_string":"Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010440425","display_name":"Gottfried Schwarz","orcid":"https://orcid.org/0000-0003-0918-7898"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gottfried Schwarz","raw_affiliation_strings":["Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany"],"affiliations":[{"raw_affiliation_string":"Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052617832","display_name":"Shiyong Cui","orcid":"https://orcid.org/0000-0002-5417-4482"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Shiyong Cui","raw_affiliation_strings":["Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany"],"affiliations":[{"raw_affiliation_string":"Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032370631","display_name":"Mihai Datcu","orcid":"https://orcid.org/0000-0002-3477-9687"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mihai Datcu","raw_affiliation_strings":["Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany"],"affiliations":[{"raw_affiliation_string":"Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany","institution_ids":["https://openalex.org/I2898391981"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5032852455"],"corresponding_institution_ids":["https://openalex.org/I2898391981"],"apc_list":null,"apc_paid":null,"fwci":0.5084,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.71820346,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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":0.996999979019165,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9828000068664551,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.7122603058815002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6968128681182861},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.690527081489563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.683564305305481},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.52679044008255},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5114094614982605},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5108354091644287},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4840668737888336},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4747267961502075},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.44286027550697327},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4166986048221588},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4143715500831604},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.412987619638443},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.35341882705688477},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.29898327589035034},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08802840113639832}],"concepts":[{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.7122603058815002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6968128681182861},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.690527081489563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.683564305305481},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.52679044008255},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5114094614982605},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5108354091644287},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4840668737888336},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4747267961502075},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.44286027550697327},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4166986048221588},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4143715500831604},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.412987619638443},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.35341882705688477},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.29898327589035034},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08802840113639832},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iwssip.2016.7502739","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwssip.2016.7502739","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Systems, Signals and Image Processing (IWSSIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:elib.dlr.de:104519","is_oa":false,"landing_page_url":"http://iwssip.stuba.sk/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Konferenzbeitrag"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1570448133","https://openalex.org/W1992969120","https://openalex.org/W2125148312","https://openalex.org/W2418871377","https://openalex.org/W6717173414"],"related_works":["https://openalex.org/W2545123933","https://openalex.org/W2585813813","https://openalex.org/W3110962985","https://openalex.org/W2042726296","https://openalex.org/W2081203575","https://openalex.org/W2096748030","https://openalex.org/W3016428515","https://openalex.org/W2160730947","https://openalex.org/W2747205507","https://openalex.org/W2917196883"],"abstract_inverted_index":{"When":[0],"we":[1,15,37,85],"perform":[2],"image":[3,13,183,200],"content":[4],"classification":[5,58,80,98,201],"by":[6,117],"appending":[7],"semantic":[8,189],"labels":[9],"to":[10,17,142],"regularly":[11],"cut":[12],"patches,":[14],"have":[16,137],"be":[18],"sure":[19],"that":[20,131],"the":[21,30,35,48,51,56,71,78,96,132,158,161,185,192],"selected":[22,52,133,193],"patch":[23,53,134],"size":[24,54,135,180],"is":[25],"a":[26,88,118,125,138,143],"good":[27],"choice":[28],"for":[29,100],"images":[31,62,106],"at":[32,39],"hand.":[33],"In":[34,82],"following,":[36],"look":[38],"SAR":[40,105,175],"(Synthetic":[41],"Aperture":[42],"Radar)":[43],"satellite":[44],"images,":[45],"and":[46,94,102,166,191],"analyse":[47],"impact":[49,140],"of":[50,77,107,121,146,157,163,187],"on":[55],"attainable":[57],"accuracy.":[59],"For":[60],"test":[61],"with":[63,149,198],"precisely":[64],"known":[65],"ground":[66],"truth,":[67],"one":[68],"can":[69],"determine":[70],"true":[72],"precision":[73],"/":[74],"recall":[75],"performance":[76],"applied":[79],"method.":[81],"our":[83],"case,":[84],"interactively":[86],"trained":[87],"classifier":[89],"system":[90],"via":[91],"active":[92,194],"learning,":[93],"compared":[95],"resulting":[97],"accuracy":[99],"high":[101,119],"medium":[103],"resolution":[104],"different":[108],"space":[109],"borne":[110],"instruments":[111],"taken":[112],"over":[113],"urban":[114],"areas,":[115],"characterized":[116],"diversity":[120],"target":[122,177],"categories.":[123],"At":[124],"first":[126],"glance,":[127],"it":[128],"turns":[129],"out":[130],"does":[136],"significant":[139],"leading":[141],"varying":[144],"number":[145,162],"identified":[147],"categories":[148,165],"strangely":[150],"related":[151],"confidence":[152,169],"levels.":[153],"A":[154],"fundamental":[155],"understanding":[156],"relationships":[159],"between":[160],"detected":[164],"their":[167],"associated":[168],"levels":[170],"requires":[171],"detailed":[172],"knowledge":[173],"about":[174],"imaging,":[176],"characteristics,":[178],"pixel":[179],"effects,":[181],"radiometric":[182],"quality,":[184],"availability":[186],"appropriate":[188],"labels,":[190],"learning":[195],"environment":[196],"together":[197],"its":[199],"tool.":[202]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2018,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
