{"id":"https://openalex.org/W3207234272","doi":"https://doi.org/10.1109/igarss47720.2021.9553272","title":"S-MobileNetV2+SegNet Model and Rapid Identification of Sugarcane","display_name":"S-MobileNetV2+SegNet Model and Rapid Identification of Sugarcane","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3207234272","doi":"https://doi.org/10.1109/igarss47720.2021.9553272","mag":"3207234272"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9553272","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553272","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","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/A5100393230","display_name":"Weiguang Liu","orcid":"https://orcid.org/0000-0002-1899-9495"},"institutions":[{"id":"https://openalex.org/I38706770","display_name":"Guilin University of Technology","ror":"https://ror.org/03z391397","country_code":"CN","type":"education","lineage":["https://openalex.org/I38706770"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiguang Liu","raw_affiliation_strings":["College of Geomatics and Geoinformation, Guilin University of Technology, Guilin, Guangxi, China","Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin, Guangxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Geomatics and Geoinformation, Guilin University of Technology, Guilin, Guangxi, China","institution_ids":["https://openalex.org/I38706770"]},{"raw_affiliation_string":"Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin, Guangxi, China","institution_ids":["https://openalex.org/I38706770"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075826136","display_name":"Guoqing Zhou","orcid":"https://orcid.org/0000-0001-8295-0496"},"institutions":[{"id":"https://openalex.org/I38706770","display_name":"Guilin University of Technology","ror":"https://ror.org/03z391397","country_code":"CN","type":"education","lineage":["https://openalex.org/I38706770"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoqing Zhou","raw_affiliation_strings":["Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin, Guangxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin, Guangxi, China","institution_ids":["https://openalex.org/I38706770"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100691526","display_name":"Jiasheng Xu","orcid":"https://orcid.org/0000-0002-2055-8947"},"institutions":[{"id":"https://openalex.org/I38706770","display_name":"Guilin University of Technology","ror":"https://ror.org/03z391397","country_code":"CN","type":"education","lineage":["https://openalex.org/I38706770"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiasheng Xu","raw_affiliation_strings":["Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin, Guangxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin, Guangxi, China","institution_ids":["https://openalex.org/I38706770"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I38706770"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3444","last_page":"3447"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9804999828338623,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9721999764442444,"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/identification","display_name":"Identification (biology)","score":0.7566846609115601},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7215250134468079},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6415473818778992},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5673884749412537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5561467409133911},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.495008647441864},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4681556224822998},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4543362259864807},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4448436200618744},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32998502254486084},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3211418390274048},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2162889540195465},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1926782727241516}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.7566846609115601},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7215250134468079},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6415473818778992},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5673884749412537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5561467409133911},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.495008647441864},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4681556224822998},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4543362259864807},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4448436200618744},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32998502254486084},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3211418390274048},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2162889540195465},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1926782727241516},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss47720.2021.9553272","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553272","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5621401100","display_name":null,"funder_award_id":"2016YFB0502501","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2888439342","https://openalex.org/W2912682610","https://openalex.org/W2963163009","https://openalex.org/W2963881378","https://openalex.org/W3033496625"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W4205302943","https://openalex.org/W2561132942","https://openalex.org/W2142795561","https://openalex.org/W2611989081","https://openalex.org/W3155418658","https://openalex.org/W4243199227"],"abstract_inverted_index":{"At":[0],"present,":[1],"there":[2],"are":[3],"many":[4],"deep":[5],"learning":[6],"models":[7],"in":[8,103],"the":[9,28,36,41,46,60,66,74,78,81,95,100,120],"identification":[10,18],"field,":[11],"but":[12],"they":[13],"usually":[14],"have":[15],"problems":[16],"with":[17,45,90,109],"accuracy":[19,96],"and":[20,34,51,80,97,112,126],"slow":[21],"speed.":[22],"In":[23],"this":[24],"paper,":[25],"we":[26],"propose":[27],"S-MobileNetV2+SegNet":[29,101,121],"model":[30,38,44,50,102,122],"to":[31,58,64,86],"identify":[32],"sugarcane,":[33],"improve":[35],"SegNet":[37],"by":[39],"replacing":[40],"encoder":[42],"VGG16":[43],"reduced":[47],"structure":[48,76],"Mobile-NetV2":[49],"introducing":[52],"different":[53],"ratios":[54],"of":[55,68,77,83,99],"dilated":[56],"convolution":[57,84],"expand":[59],"local":[61],"receptive":[62],"field":[63],"eliminate":[65],"problem":[67],"insufficient":[69],"information":[70],"capture.":[71],"Then":[72],"reduce":[73],"network":[75,89],"decoder":[79],"number":[82],"kernels":[85],"achieve":[87],"a":[88],"fewer":[91],"parameters.":[92],"To":[93],"verify":[94],"speed":[98],"sugarcane":[104,129],"identification,":[105],"it":[106],"is":[107],"compared":[108],"SegNet,":[110],"DeepLabV3+,":[111],"DeepLab-V3+Mobile-NetV2":[113],"models.":[114],"The":[115],"experimental":[116],"results":[117,125],"show":[118],"that":[119],"has":[123],"better":[124],"performance":[127],"for":[128],"identification.":[130]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}