{"id":"https://openalex.org/W2983707810","doi":"https://doi.org/10.1109/igarss.2019.8899214","title":"An Active Deep Learning Approach for Minimally-Supervised Polsar Image Classification","display_name":"An Active Deep Learning Approach for Minimally-Supervised Polsar Image Classification","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2983707810","doi":"https://doi.org/10.1109/igarss.2019.8899214","mag":"2983707810"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8899214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 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/A5107997096","display_name":"Haixia Bi","orcid":"https://orcid.org/0000-0002-3629-0332"},"institutions":[{"id":"https://openalex.org/I22128151","display_name":"University of Derby","ror":"https://ror.org/02yhrrk59","country_code":"GB","type":"education","lineage":["https://openalex.org/I22128151"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Haixia Bi","raw_affiliation_strings":["College of Engineering and Technology, University of Derby, Derby, United Kingdom"],"affiliations":[{"raw_affiliation_string":"College of Engineering and Technology, University of Derby, Derby, United Kingdom","institution_ids":["https://openalex.org/I22128151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071461704","display_name":"Feng Xu","orcid":"https://orcid.org/0000-0002-7015-1467"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Xu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074077175","display_name":"Zhiqiang Wei","orcid":"https://orcid.org/0000-0003-3400-5590"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiqiang Wei","raw_affiliation_strings":["Xi\u2019an Electronics and Engineering Institute, Xi\u2019an, China","Xi'an Electronics and Engineering Institute, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi\u2019an Electronics and Engineering Institute, Xi\u2019an, China","institution_ids":[]},{"raw_affiliation_string":"Xi'an Electronics and Engineering Institute, Xi'an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000694997","display_name":"Yibo Han","orcid":"https://orcid.org/0000-0003-0863-3040"},"institutions":[{"id":"https://openalex.org/I4210115515","display_name":"Nanyang Institute of Technology","ror":"https://ror.org/0203c2755","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115515"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibo Han","raw_affiliation_strings":["Nanyang Institute of Technology, Nanyang, China"],"affiliations":[{"raw_affiliation_string":"Nanyang Institute of Technology, Nanyang, China","institution_ids":["https://openalex.org/I4210115515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087264354","display_name":"Yuanlong Cui","orcid":"https://orcid.org/0000-0003-2417-4251"},"institutions":[{"id":"https://openalex.org/I22128151","display_name":"University of Derby","ror":"https://ror.org/02yhrrk59","country_code":"GB","type":"education","lineage":["https://openalex.org/I22128151"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yuanlong Cui","raw_affiliation_strings":["College of Engineering and Technology, University of Derby, Derby, United Kingdom"],"affiliations":[{"raw_affiliation_string":"College of Engineering and Technology, University of Derby, Derby, United Kingdom","institution_ids":["https://openalex.org/I22128151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102873217","display_name":"Yong Xue","orcid":"https://orcid.org/0000-0002-3852-7831"},"institutions":[{"id":"https://openalex.org/I22128151","display_name":"University of Derby","ror":"https://ror.org/02yhrrk59","country_code":"GB","type":"education","lineage":["https://openalex.org/I22128151"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yong Xue","raw_affiliation_strings":["College of Engineering and Technology, University of Derby, Derby, United Kingdom"],"affiliations":[{"raw_affiliation_string":"College of Engineering and Technology, University of Derby, Derby, United Kingdom","institution_ids":["https://openalex.org/I22128151"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113541537","display_name":"Zongben Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongben Xu","raw_affiliation_strings":["Xi\u2019an Jiaotong University, Xi\u2019an, China","Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5107997096"],"corresponding_institution_ids":["https://openalex.org/I22128151"],"apc_list":null,"apc_paid":null,"fwci":11.1077,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.98323681,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3185","last_page":"3188"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11698","display_name":"Underwater Acoustics Research","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8054034113883972},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8032669425010681},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7233249545097351},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7098950743675232},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.6215256452560425},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5874432325363159},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5802045464515686},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5607673525810242},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5496063828468323},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.519472062587738},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.4434683918952942},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30543792247772217},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.21057602763175964}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8054034113883972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8032669425010681},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7233249545097351},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7098950743675232},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.6215256452560425},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5874432325363159},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5802045464515686},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5607673525810242},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5496063828468323},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.519472062587738},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.4434683918952942},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30543792247772217},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.21057602763175964},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8899214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1588783521","https://openalex.org/W1967455454","https://openalex.org/W1987110781","https://openalex.org/W1996140089","https://openalex.org/W2016860790","https://openalex.org/W2016890032","https://openalex.org/W2062432961","https://openalex.org/W2062915026","https://openalex.org/W2078985447","https://openalex.org/W2095595743","https://openalex.org/W2100495367","https://openalex.org/W2100566779","https://openalex.org/W2101365302","https://openalex.org/W2107131609","https://openalex.org/W2110798204","https://openalex.org/W2112130876","https://openalex.org/W2112796928","https://openalex.org/W2113464037","https://openalex.org/W2124244761","https://openalex.org/W2130762895","https://openalex.org/W2132012856","https://openalex.org/W2144554203","https://openalex.org/W2150045166","https://openalex.org/W2152214791","https://openalex.org/W2155342973","https://openalex.org/W2164296623","https://openalex.org/W2164325628","https://openalex.org/W2169282664","https://openalex.org/W2169551590","https://openalex.org/W2198260271","https://openalex.org/W2248623186","https://openalex.org/W2304841027","https://openalex.org/W2306802236","https://openalex.org/W2337429362","https://openalex.org/W2345055757","https://openalex.org/W2370317051","https://openalex.org/W2492018752","https://openalex.org/W2524453835","https://openalex.org/W2526969612","https://openalex.org/W2559324447","https://openalex.org/W2595144186","https://openalex.org/W2611452721","https://openalex.org/W2696603875","https://openalex.org/W2750023899","https://openalex.org/W2754361766","https://openalex.org/W2771450566","https://openalex.org/W2782522152","https://openalex.org/W2785787385","https://openalex.org/W2787919999","https://openalex.org/W2821322924","https://openalex.org/W2892719431","https://openalex.org/W2897760800","https://openalex.org/W2914331073","https://openalex.org/W2917032349","https://openalex.org/W3104795559","https://openalex.org/W6635188891","https://openalex.org/W6678669864"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661","https://openalex.org/W2147064750"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"improving":[2],"the":[3,56,65,69,76,81,99],"classification":[4,110],"performance":[5,77],"with":[6,112],"greatly":[7],"reduced":[8,114],"annotation":[9,115],"cost,":[10],"this":[11],"paper":[12],"presents":[13],"an":[14],"active":[15,26],"deep":[16],"learning":[17,27],"approach":[18,107],"for":[19,60],"minimally-supervised":[20],"PolSAR":[21],"image":[22],"classification,":[23],"which":[24],"integrates":[25],"and":[28,53,62,78,93],"fine-tuning":[29],"convolutional":[30],"neural":[31],"network":[32],"(CNN)":[33],"into":[34],"a":[35,40,44],"principled":[36],"framework.":[37],"Starting":[38],"from":[39],"CNN":[41,66],"trained":[42],"using":[43],"very":[45],"limited":[46],"number":[47],"of":[48,80],"labeled":[49],"pixels,":[50],"we":[51,84],"iteratively":[52],"actively":[54],"select":[55],"most":[57],"informative":[58],"candidates":[59],"annotation,":[61],"incrementally":[63],"fine-tune":[64],"by":[67],"incorporating":[68],"newly":[70],"annotated":[71],"pixels.":[72],"Moreover,":[73],"to":[74,89,97],"boost":[75],"robustness":[79],"proposed":[82],"method,":[83],"employ":[85],"Markov":[86],"random":[87],"field":[88],"enforce":[90],"label":[91],"smoothness,":[92],"data":[94],"augmentation":[95],"technique":[96],"enlarge":[98],"training":[100],"set.":[101],"Extensive":[102],"experiments":[103],"demonstrated":[104],"that":[105],"our":[106],"achieved":[108],"state-of-the-art":[109],"results":[111],"significantly":[113],"cost.":[116]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
