{"id":"https://openalex.org/W2901025777","doi":"https://doi.org/10.1109/igarss.2018.8517872","title":"D-Atr Via Deep Neural Network for Large Scene Sar Images","display_name":"D-Atr Via Deep Neural Network for Large Scene Sar Images","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901025777","doi":"https://doi.org/10.1109/igarss.2018.8517872","mag":"2901025777"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8517872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517872","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":"conference-paper","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/A5021918738","display_name":"Cui Tang","orcid":"https://orcid.org/0000-0002-5675-5440"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cui Tang","raw_affiliation_strings":["School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061245960","display_name":"Zongyong Cui","orcid":"https://orcid.org/0000-0003-1155-786X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongyong Cui","raw_affiliation_strings":["School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003057872","display_name":"Nengyuan Liu","orcid":"https://orcid.org/0000-0002-2827-3321"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nengyuan Liu","raw_affiliation_strings":["School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019411747","display_name":"Zongjie Cao","orcid":"https://orcid.org/0000-0002-0117-9087"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongjie Cao","raw_affiliation_strings":["School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2326","last_page":"2329"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9998999834060669,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9998999834060669,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9987000226974487,"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":0.9966999888420105,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8313298225402832},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8154415488243103},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.7255783677101135},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7127161026000977},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.630367636680603},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6165012121200562},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.585435152053833},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5836502313613892},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5349861979484558},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5167826414108276},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.513780415058136},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5025560855865479},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.45716914534568787},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3435385227203369}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8313298225402832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8154415488243103},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.7255783677101135},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7127161026000977},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.630367636680603},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6165012121200562},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.585435152053833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5836502313613892},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5349861979484558},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5167826414108276},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.513780415058136},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5025560855865479},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.45716914534568787},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3435385227203369},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8517872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517872","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":[{"display_name":"Reduced inequalities","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/10"},{"display_name":"Peace, Justice and strong institutions","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W322998299","https://openalex.org/W1536680647","https://openalex.org/W2052172955","https://openalex.org/W2124648367","https://openalex.org/W2144158572","https://openalex.org/W2148791593","https://openalex.org/W2154610955","https://openalex.org/W2410591237","https://openalex.org/W2771176499","https://openalex.org/W2790238224","https://openalex.org/W2963037989","https://openalex.org/W3106250896","https://openalex.org/W6611190527","https://openalex.org/W6628973269","https://openalex.org/W6682713193","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W3137365474","https://openalex.org/W2886347302","https://openalex.org/W2784759481","https://openalex.org/W1545594509","https://openalex.org/W2540523933","https://openalex.org/W3038591045","https://openalex.org/W3130755980","https://openalex.org/W2540650467","https://openalex.org/W4380446815","https://openalex.org/W2773828237"],"abstract_inverted_index":{"Directly":[0],"automatic":[1],"target":[2,73],"recognition":[3],"(D-ATR)":[4],"for":[5,62],"large":[6,91,115],"scene":[7,92,116],"SAR":[8,26,72,93,117],"images":[9,94],"based":[10],"on":[11,108],"a":[12,83,100,123],"deep":[13,102],"neural":[14,104],"network":[15,105],"is":[16,59],"proposed":[17,76],"in":[18,25,90,99],"this":[19],"paper.":[20],"To":[21],"recognize":[22,88],"the":[23,28,45,49,54,67,112],"targets":[24,89],"images,":[27],"traditional":[29],"methods":[30],"contains":[31],"four":[32],"steps:":[33],"detection,":[34],"discrimination,":[35],"feature":[36],"extraction":[37],"and":[38,57,86,111],"classification.":[39],"These":[40],"processes":[41],"are":[42],"independent":[43],"but":[44],"processing":[46,63,125],"result":[47],"from":[48],"previous":[50],"step":[51],"will":[52],"affect":[53],"next":[55],"step,":[56],"there":[58],"still":[60],"room":[61],"speed":[64],"improvement":[65],"of":[66,71],"latest":[68],"integrated":[69],"system":[70,85],"detection.":[74],"The":[75],"method":[77],"can":[78],"integrate":[79],"these":[80],"steps":[81],"as":[82],"whole":[84],"directly":[87],"by":[95],"encapsulating":[96],"all":[97],"computation":[98],"single":[101],"convolutional":[103],"(DCNN).":[106],"Experiments":[107],"MSTAR":[109],"dataset":[110],"1478\u00d71784":[113],"simulated":[114],"image":[118],"show":[119],"high":[120],"accuracy":[121],"with":[122],"fast":[124],"speed.":[126]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
