{"id":"https://openalex.org/W4224269597","doi":"https://doi.org/10.3390/rs14091956","title":"CCTNet: Coupled CNN and Transformer Network for Crop Segmentation of Remote Sensing Images","display_name":"CCTNet: Coupled CNN and Transformer Network for Crop Segmentation of Remote Sensing Images","publication_year":2022,"publication_date":"2022-04-19","ids":{"openalex":"https://openalex.org/W4224269597","doi":"https://doi.org/10.3390/rs14091956"},"language":"en","primary_location":{"id":"doi:10.3390/rs14091956","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14091956","pdf_url":"https://www.mdpi.com/2072-4292/14/9/1956/pdf?version=1650353545","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/9/1956/pdf?version=1650353545","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003334716","display_name":"Hong Wang","orcid":"https://orcid.org/0000-0002-7780-1661"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Wang","raw_affiliation_strings":["School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101499468","display_name":"Xianzhong Chen","orcid":"https://orcid.org/0000-0003-4113-6994"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianzhong Chen","raw_affiliation_strings":["Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China","School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China","Shunde Graduate School of University of Science and Technology Beijing, Foshan 528000, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China","institution_ids":[]},{"raw_affiliation_string":"School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I92403157"]},{"raw_affiliation_string":"Shunde Graduate School of University of Science and Technology Beijing, Foshan 528000, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100712692","display_name":"Tianxiang Zhang","orcid":"https://orcid.org/0000-0002-0996-2586"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianxiang Zhang","raw_affiliation_strings":["Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China","School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China","institution_ids":[]},{"raw_affiliation_string":"School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100642952","display_name":"Zhiyong Xu","orcid":"https://orcid.org/0000-0002-3210-8839"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Xu","raw_affiliation_strings":["Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China","School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China","institution_ids":[]},{"raw_affiliation_string":"School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074215202","display_name":"Jiangyun Li","orcid":"https://orcid.org/0000-0003-2288-7901"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiangyun Li","raw_affiliation_strings":["Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China","School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China","Shunde Graduate School of University of Science and Technology Beijing, Foshan 528000, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing 100083, China","institution_ids":[]},{"raw_affiliation_string":"School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I92403157"]},{"raw_affiliation_string":"Shunde Graduate School of University of Science and Technology Beijing, Foshan 528000, China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5074215202"],"corresponding_institution_ids":["https://openalex.org/I92403157"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":22.9499,"has_fulltext":true,"cited_by_count":117,"citation_normalized_percentile":{"value":0.9967313,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"14","issue":"9","first_page":"1956","last_page":"1956"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9998000264167786,"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":0.9998000264167786,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9896000027656555,"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/computer-science","display_name":"Computer science","score":0.7835381031036377},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6816526651382446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6654385328292847},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.599436342716217},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5522845983505249},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.49837446212768555},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47712278366088867},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4057283401489258}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7835381031036377},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6816526651382446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6654385328292847},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.599436342716217},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5522845983505249},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.49837446212768555},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47712278366088867},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4057283401489258},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14091956","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14091956","pdf_url":"https://www.mdpi.com/2072-4292/14/9/1956/pdf?version=1650353545","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6fc6b8e76fa6448ca466b8b8266d901e","is_oa":true,"landing_page_url":"https://doaj.org/article/6fc6b8e76fa6448ca466b8b8266d901e","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 9, p 1956 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/9/1956/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14091956","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 14; Issue 9; Pages: 1956","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14091956","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14091956","pdf_url":"https://www.mdpi.com/2072-4292/14/9/1956/pdf?version=1650353545","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[{"id":"https://openalex.org/G6389130447","display_name":null,"funder_award_id":"FRF-DF-19-002","funder_id":"https://openalex.org/F4320325365","funder_display_name":"University of Science and Technology Beijing"}],"funders":[{"id":"https://openalex.org/F4320325365","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4224269597.pdf","grobid_xml":"https://content.openalex.org/works/W4224269597.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2013414890","https://openalex.org/W2097117768","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2565950292","https://openalex.org/W2884585870","https://openalex.org/W2916798096","https://openalex.org/W2955058313","https://openalex.org/W2961348656","https://openalex.org/W2964309882","https://openalex.org/W2964350391","https://openalex.org/W3035433720","https://openalex.org/W3040608330","https://openalex.org/W3097121762","https://openalex.org/W3115164315","https://openalex.org/W3121069613","https://openalex.org/W3130695101","https://openalex.org/W3138516171","https://openalex.org/W3160694286","https://openalex.org/W3170841864","https://openalex.org/W3171087525","https://openalex.org/W3172509117","https://openalex.org/W3176945377","https://openalex.org/W3196904463","https://openalex.org/W3200870516","https://openalex.org/W4206706211","https://openalex.org/W4214719356","https://openalex.org/W4226013274","https://openalex.org/W4295308583","https://openalex.org/W4313007769","https://openalex.org/W6684191040","https://openalex.org/W6797790494"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2055243143","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W4206178588","https://openalex.org/W4287635093","https://openalex.org/W3094491777","https://openalex.org/W3214715529"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,19,45,257],"by":[2,138,144,258],"using":[3],"remote":[4,259],"sensing":[5,260],"images":[6,56],"is":[7,244],"an":[8],"efficient":[9],"method":[10,254],"for":[11,42,255],"agricultural":[12],"crop":[13,18,44,87,256],"classification.":[14],"Recent":[15],"solutions":[16],"in":[17,203],"are":[20,38,170,194],"mainly":[21],"deep-learning-based":[22],"methods,":[23,231],"including":[24],"two":[25,36,154],"mainstream":[26],"architectures:":[27],"Convolutional":[28],"Neural":[29],"Networks":[30],"(CNNs)":[31],"and":[32,109,113,125,136,141,163,191,200,207],"Transformer.":[33],"However,":[34],"these":[35,176],"architectures":[37],"not":[39],"sufficiently":[40],"good":[41],"the":[43,49,54,69,79,86,98,106,122,131,139,149,157,164,204,216,223,226,247],"task":[46],"due":[47],"to":[48,58,68,94,101,146,173,196],"following":[50],"three":[51,179],"reasons.":[52],"First,":[53],"ultra-high-resolution":[55],"need":[57,100],"be":[59,90,102,251],"cut":[60],"into":[61],"small":[62,110,198],"patches":[63,99],"before":[64],"processing,":[65],"which":[66,129],"leads":[67],"incomplete":[70],"structure":[71],"of":[72,78,81],"different":[73],"categories\u2019":[74],"edges.":[75],"Second,":[76],"because":[77],"deficiency":[80],"global":[82,142],"information,":[83],"categories":[84],"inside":[85],"field":[88],"may":[89],"wrongly":[91],"classified.":[92],"Third,":[93],"restore":[95,208],"complete":[96,209],"images,":[97],"spliced":[103],"together,":[104],"causing":[105],"edge":[107,135],"artifacts":[108],"misclassified":[111],"objects":[112,199],"holes.":[114],"Therefore,":[115],"we":[116],"proposed":[117,195,248],"a":[118,241,252],"novel":[119],"architecture":[120],"named":[121,182],"Coupled":[123,165],"CNN":[124,140,228],"Transformer":[126,145,230],"Network":[127],"(CCTNet),":[128],"combines":[130],"local":[132],"details":[133],"(e.g.,":[134],"texture)":[137],"context":[143],"cope":[147],"with":[148],"aforementioned":[150],"problems.":[151],"In":[152],"particular,":[153],"modules,":[155],"namely":[156],"Light":[158],"Adaptive":[159],"Fusion":[160,167],"Module":[161,168],"(LAFM)":[162],"Attention":[166],"(CAFM),":[169],"also":[171],"designed":[172],"efficiently":[174],"fuse":[175],"advantages.":[177],"Meanwhile,":[178],"effective":[180],"methods":[181],"Overlapping":[183],"Sliding":[184],"Window":[185],"(OSW),":[186],"Testing":[187],"Time":[188],"Augmentation":[189],"(TTA),":[190],"Post-Processing":[192],"(PP)":[193],"remove":[197],"holes":[201],"embedded":[202],"inference":[205],"stage":[206],"images.":[210,261],"The":[211],"experimental":[212],"results":[213],"evaluated":[214],"on":[215],"Barley":[217],"Remote":[218],"Sensing":[219],"Dataset":[220],"present":[221],"that":[222,246],"CCTNet":[224,249],"outperformed":[225],"single":[227],"or":[229],"achieving":[232],"72.97%":[233],"mean":[234],"Intersection":[235],"over":[236],"Union":[237],"(mIoU)":[238],"scores.":[239],"As":[240],"consequence,":[242],"it":[243],"believed":[245],"can":[250],"competitive":[253]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":35},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":41},{"year":2022,"cited_by_count":5}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2022-04-26T00:00:00"}