{"id":"https://openalex.org/W7134130960","doi":"https://doi.org/10.1016/j.compag.2026.111627","title":"Synergistic fusion network of GAN-based deblurring and target detection for high-speed potato seeding monitoring","display_name":"Synergistic fusion network of GAN-based deblurring and target detection for high-speed potato seeding monitoring","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7134130960","doi":"https://doi.org/10.1016/j.compag.2026.111627"},"language":"en","primary_location":{"id":"doi:10.1016/j.compag.2026.111627","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compag.2026.111627","pdf_url":null,"source":{"id":"https://openalex.org/S116775814","display_name":"Computers and Electronics in Agriculture","issn_l":"0168-1699","issn":["0168-1699","1872-7107"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers and Electronics in Agriculture","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.compag.2026.111627","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122284737","display_name":"Da Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Da Wang","raw_affiliation_strings":["College of Engineering, China Agricultural University, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128297117","display_name":"Xu Mao","orcid":null},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xu Mao","raw_affiliation_strings":["College of Engineering, China Agricultural University, Beijing 100083, China","State Key Laboratory of Intelligent Agricultural Power Equipment, Beijing 100083, China"],"raw_orcid":"https://orcid.org/0000-0002-7493-0505","affiliations":[{"raw_affiliation_string":"College of Engineering, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"State Key Laboratory of Intelligent Agricultural Power Equipment, Beijing 100083, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111252361","display_name":"Sanhui Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sanhui Wang","raw_affiliation_strings":["College of Engineering, China Agricultural University, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124981563","display_name":"Jidong Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jidong Lv","raw_affiliation_strings":["College of Engineering, China Agricultural University, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128322677","display_name":"Yang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["MENOBLE Co., Ltd., Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MENOBLE Co., Ltd., Beijing 100083, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767708","display_name":"Yong Tan","orcid":"https://orcid.org/0000-0002-2526-1640"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Tan","raw_affiliation_strings":["College of Engineering, China Agricultural University, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, China Agricultural University, Beijing 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122222042","display_name":"Fozilov Golibjon","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109462","display_name":"Tashkent Institute of Irrigation and Agricultural Mechanization Engineers","ror":"https://ror.org/01s4mx151","country_code":"UZ","type":"education","lineage":["https://openalex.org/I4210109462"]}],"countries":["UZ"],"is_corresponding":false,"raw_author_name":"Fozilov Golibjon","raw_affiliation_strings":["Department of Agricultural Machinery and Technologies, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University, Tashkent 100000, Uzbekistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Agricultural Machinery and Technologies, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University, Tashkent 100000, Uzbekistan","institution_ids":["https://openalex.org/I4210109462"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5128297117"],"corresponding_institution_ids":["https://openalex.org/I52158045"],"apc_list":{"value":3680,"currency":"USD","value_usd":3680},"apc_paid":{"value":3680,"currency":"USD","value_usd":3680},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28773504,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"246","issue":null,"first_page":"111627","last_page":"111627"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9182000160217285,"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":0.9182000160217285,"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":0.0142000000923872,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.013100000098347664,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deblurring","display_name":"Deblurring","score":0.8603000044822693},{"id":"https://openalex.org/keywords/seeding","display_name":"Seeding","score":0.6615999937057495},{"id":"https://openalex.org/keywords/motion-blur","display_name":"Motion blur","score":0.5220999717712402},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.4975999891757965},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4422999918460846},{"id":"https://openalex.org/keywords/fusion-mechanism","display_name":"Fusion mechanism","score":0.43860000371932983},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.38100001215934753},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.37119999527931213},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.3682999908924103}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.8603000044822693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6937000155448914},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6786999702453613},{"id":"https://openalex.org/C36248471","wikidata":"https://www.wikidata.org/wiki/Q7445669","display_name":"Seeding","level":2,"score":0.6615999937057495},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5723000168800354},{"id":"https://openalex.org/C2777708103","wikidata":"https://www.wikidata.org/wiki/Q852589","display_name":"Motion blur","level":3,"score":0.5220999717712402},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.4975999891757965},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4422999918460846},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.43860000371932983},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.37119999527931213},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3682999908924103},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3483999967575073},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3165999948978424},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.31060001254081726},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.30160000920295715},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28619998693466187},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.27480000257492065},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2540000081062317},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.compag.2026.111627","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compag.2026.111627","pdf_url":null,"source":{"id":"https://openalex.org/S116775814","display_name":"Computers and Electronics in Agriculture","issn_l":"0168-1699","issn":["0168-1699","1872-7107"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers and Electronics in Agriculture","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.compag.2026.111627","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compag.2026.111627","pdf_url":null,"source":{"id":"https://openalex.org/S116775814","display_name":"Computers and Electronics in Agriculture","issn_l":"0168-1699","issn":["0168-1699","1872-7107"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers and Electronics in Agriculture","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321540","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2781120606","https://openalex.org/W2963312584","https://openalex.org/W2964042483","https://openalex.org/W3004133675","https://openalex.org/W3072351143","https://openalex.org/W3109908659","https://openalex.org/W4307771774","https://openalex.org/W4312083440","https://openalex.org/W4323340581","https://openalex.org/W4386072458","https://openalex.org/W4388550560","https://openalex.org/W4393942577","https://openalex.org/W4399459160","https://openalex.org/W4401559026","https://openalex.org/W4402754006","https://openalex.org/W4403000898","https://openalex.org/W4405282523","https://openalex.org/W4409866382","https://openalex.org/W4412915895","https://openalex.org/W4414853600","https://openalex.org/W7092365961"],"related_works":[],"abstract_inverted_index":{"Real-time,":[0],"accurate":[1],"monitoring":[2],"of":[3,31,88,93,125],"potato":[4,73],"miss-":[5],"and":[6,67,90,104,113,156,162],"multi-seeding":[7],"is":[8,178],"critical":[9],"for":[10,135,159],"precision":[11,160],"seeding,":[12],"but":[13],"challenged":[14],"by":[15,19,57,109],"motion":[16,186],"blur":[17,26],"induced":[18],"high-speed":[20,72],"seed":[21],"metering.":[22],"Severe":[23],"non-uniform,":[24],"multi-scale":[25],"causes":[27],"a":[28,45,58,91,122],"substantial":[29],"loss":[30],"semantically":[32],"discriminative":[33],"features,":[34],"rendering":[35],"conventional":[36],"\u201cdeblur-then-detect\u201d":[37],"pipelines":[38],"ineffective.":[39],"To":[40],"overcome":[41],"this,":[42],"we":[43],"propose":[44],"novel":[46],"end-to-end":[47],"GAN":[48],"(Generative":[49],"Adversarial":[50],"Network)-based":[51],"deblurring\u2013target":[52],"detection":[53,105,183],"(GDTD)":[54],"framework,":[55],"underpinned":[56],"synergistic":[59],"training":[60],"mechanism":[61],"that":[62,170],"jointly":[63],"optimizes":[64],"image":[65],"restoration":[66],"object":[68],"detection.":[69],"Evaluated":[70],"under":[71,184],"seeding":[74,161],"conditions":[75],"with":[76,128],"dynamic":[77,164],"non-uniform":[78],"blur,":[79],"The":[80],"GDTD":[81],"achieved":[82],"an":[83],"mAP@0.5:0.95":[84],"(mean":[85],"Average":[86],"Precision)":[87],"0.6843":[89],"Precision":[92],"0.9115,":[94],"outperforming":[95],"two-stage":[96],"fusion":[97],"frameworks":[98],"built":[99],"on":[100],"state-of-the-art":[101],"deblurring":[102],"(TSF-DeblurGAN)":[103],"(YOLO-based":[106],"LGCSA-Detector)":[107],"models":[108],"up":[110],"to":[111,147,181],"19.7%":[112],"5.73%,":[114],"respectively.":[115],"Furthermore,":[116],"it":[117,133],"sustained":[118],"real-time":[119],"inference":[120],"at":[121],"processing":[123],"speed":[124],"27.3":[126],"FPS":[127],"low":[129],"power":[130],"consumption,":[131],"making":[132],"suitable":[134],"embedded":[136],"agricultural":[137],"devices.":[138],"By":[139],"shifting":[140],"the":[141,179],"optimization":[142],"paradigm":[143],"from":[144],"pixel-level":[145],"fidelity":[146],"task-aware":[148],"semantic":[149,172],"restoration,":[150,173],"this":[151],"study":[152],"provides":[153],"important":[154],"theoretical":[155],"practical":[157],"support":[158],"other":[163],"scenarios":[165],"in":[166],"smart":[167],"agriculture,":[168],"demonstrating":[169],"task-driven":[171],"rather":[174],"than":[175],"pixel-perfect":[176],"deblurring,":[177],"key":[180],"robust":[182],"extreme":[185],"blur.":[187]},"counts_by_year":[],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2026-03-08T00:00:00"}