{"id":"https://openalex.org/W4416054120","doi":"https://doi.org/10.3389/fcomp.2025.1551326","title":"UAV-based estimation of post-sowing rice plant density using RGB imagery and deep learning across multiple altitudes","display_name":"UAV-based estimation of post-sowing rice plant density using RGB imagery and deep learning across multiple altitudes","publication_year":2025,"publication_date":"2025-07-11","ids":{"openalex":"https://openalex.org/W4416054120","doi":"https://doi.org/10.3389/fcomp.2025.1551326"},"language":"en","primary_location":{"id":"doi:10.3389/fcomp.2025.1551326","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fcomp.2025.1551326","pdf_url":"https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2025.1551326/pdf","source":{"id":"https://openalex.org/S4210211086","display_name":"Frontiers in Computer Science","issn_l":"2624-9898","issn":["2624-9898"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2025.1551326/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039991207","display_name":"Tr\u1ecdng Hi\u1ebfu L\u01b0u","orcid":"https://orcid.org/0000-0002-8145-9854"},"institutions":[{"id":"https://openalex.org/I177733328","display_name":"Can Tho University","ror":"https://ror.org/0071qz696","country_code":"VN","type":"education","lineage":["https://openalex.org/I177733328"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Trong Hieu Luu","raw_affiliation_strings":["College of Engineering, Can Tho University, Can Tho, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, Can Tho University, Can Tho, Vietnam","institution_ids":["https://openalex.org/I177733328"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Thanh Tam Nguyen","orcid":null},"institutions":[{"id":"https://openalex.org/I177733328","display_name":"Can Tho University","ror":"https://ror.org/0071qz696","country_code":"VN","type":"education","lineage":["https://openalex.org/I177733328"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Thanh Tam Nguyen","raw_affiliation_strings":["Mekong Delta Development Research Institute, Can Tho University, Can Tho, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mekong Delta Development Research Institute, Can Tho University, Can Tho, Vietnam","institution_ids":["https://openalex.org/I177733328"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003690110","display_name":"Quang Hieu Ngo","orcid":"https://orcid.org/0000-0002-7537-9049"},"institutions":[{"id":"https://openalex.org/I177733328","display_name":"Can Tho University","ror":"https://ror.org/0071qz696","country_code":"VN","type":"education","lineage":["https://openalex.org/I177733328"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Quang Hieu Ngo","raw_affiliation_strings":["College of Engineering, Can Tho University, Can Tho, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, Can Tho University, Can Tho, Vietnam","institution_ids":["https://openalex.org/I177733328"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Huu Cuong Nguyen","orcid":null},"institutions":[{"id":"https://openalex.org/I177733328","display_name":"Can Tho University","ror":"https://ror.org/0071qz696","country_code":"VN","type":"education","lineage":["https://openalex.org/I177733328"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Huu Cuong Nguyen","raw_affiliation_strings":["College of Engineering, Can Tho University, Can Tho, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, Can Tho University, Can Tho, Vietnam","institution_ids":["https://openalex.org/I177733328"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080808397","display_name":"Phan Nguyen Ky Phuc","orcid":"https://orcid.org/0000-0001-5639-7527"},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Phan Nguyen Ky Phuc","raw_affiliation_strings":["School of Industrial Engineering and Management Department, International University \u2013 Vietnam National University, Ho Chi Minh City, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Industrial Engineering and Management Department, International University \u2013 Vietnam National University, Ho Chi Minh City, Vietnam","institution_ids":["https://openalex.org/I123565023"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5003690110"],"corresponding_institution_ids":["https://openalex.org/I177733328"],"apc_list":{"value":1150,"currency":"USD","value_usd":1150},"apc_paid":{"value":1150,"currency":"USD","value_usd":1150},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28058293,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.7738999724388123,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.7738999724388123,"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/T10616","display_name":"Smart Agriculture and AI","score":0.08489999920129776,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.012900000438094139,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6176999807357788},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5271000266075134},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5109000205993652},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.49140000343322754},{"id":"https://openalex.org/keywords/precision-agriculture","display_name":"Precision agriculture","score":0.47859999537467957},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4781999886035919},{"id":"https://openalex.org/keywords/altitude","display_name":"Altitude (triangle)","score":0.4336000084877014},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.4235999882221222},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3840999901294708}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6176999807357788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6079999804496765},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5508000254631042},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5346999764442444},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5271000266075134},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.49140000343322754},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.47859999537467957},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4781999886035919},{"id":"https://openalex.org/C6350597","wikidata":"https://www.wikidata.org/wiki/Q339495","display_name":"Altitude (triangle)","level":2,"score":0.4336000084877014},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.4235999882221222},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3840999901294708},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37299999594688416},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.35510000586509705},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.32659998536109924},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3230000138282776},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.32249999046325684},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3183000087738037},{"id":"https://openalex.org/C85582077","wikidata":"https://www.wikidata.org/wiki/Q842623","display_name":"Paddy field","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C117455697","wikidata":"https://www.wikidata.org/wiki/Q190149","display_name":"Photogrammetry","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.2831000089645386},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2770000100135803},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.26570001244544983}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3389/fcomp.2025.1551326","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fcomp.2025.1551326","pdf_url":"https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2025.1551326/pdf","source":{"id":"https://openalex.org/S4210211086","display_name":"Frontiers in Computer Science","issn_l":"2624-9898","issn":["2624-9898"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:063354e066bb4957bd8ad265fb148e99","is_oa":true,"landing_page_url":"https://doaj.org/article/063354e066bb4957bd8ad265fb148e99","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Computer Science, Vol 7 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fcomp.2025.1551326","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fcomp.2025.1551326","pdf_url":"https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2025.1551326/pdf","source":{"id":"https://openalex.org/S4210211086","display_name":"Frontiers in Computer Science","issn_l":"2624-9898","issn":["2624-9898"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4416054120.pdf"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W2066416082","https://openalex.org/W2121064498","https://openalex.org/W2604795894","https://openalex.org/W2616262716","https://openalex.org/W2892250657","https://openalex.org/W2901211013","https://openalex.org/W2915159483","https://openalex.org/W2934229382","https://openalex.org/W2939018547","https://openalex.org/W2940452602","https://openalex.org/W2943149949","https://openalex.org/W3013956155","https://openalex.org/W3047115829","https://openalex.org/W3144503735","https://openalex.org/W3162117813","https://openalex.org/W3178598619","https://openalex.org/W3180151162","https://openalex.org/W3194765271","https://openalex.org/W3196766153","https://openalex.org/W3210703231","https://openalex.org/W4200176285","https://openalex.org/W4200250223","https://openalex.org/W4244627517","https://openalex.org/W4282837814","https://openalex.org/W4366085631","https://openalex.org/W4372295151","https://openalex.org/W4380995961","https://openalex.org/W4385955446","https://openalex.org/W4386891052","https://openalex.org/W4398810114","https://openalex.org/W4404579104","https://openalex.org/W4406843372","https://openalex.org/W4407009473","https://openalex.org/W4409173044"],"related_works":[],"abstract_inverted_index":{"This":[0,186],"study":[1],"presents":[2],"a":[3,73,89,111,132,136,141,158,166],"novel":[4],"and":[5,30,40,49,61,106,127,135,202,220],"efficient":[6],"approach":[7],"to":[8,28,47,213],"accurately":[9,118],"assess":[10],"post-sowing":[11],"rice":[12,79,101,172,208],"plant":[13,80,173],"density":[14,81,174],"by":[15],"leveraging":[16],"unmanned":[17],"aerial":[18],"vehicles":[19],"(UAVs)":[20],"equipped":[21],"with":[22,171,179],"high-resolution":[23],"RGB":[24],"cameras.":[25],"In":[26],"contrast":[27],"labor-intensive":[29],"spatially":[31,200],"limited":[32],"traditional":[33,183],"methods":[34],"that":[35,98,157,176],"rely":[36],"on":[37],"manual":[38],"sampling":[39],"extrapolation,":[41],"our":[42,154],"proposed":[43],"methodology":[44],"uses":[45],"UAVs":[46],"rapidly":[48],"comprehensively":[50],"survey":[51],"entire":[52],"paddy":[53],"fields":[54],"at":[55],"optimized":[56],"altitudes":[57],"(4,":[58],"6,":[59],"8,":[60],"10":[62],"m).":[63],"Aerial":[64],"imagery":[65],"was":[66],"autonomously":[67],"acquired":[68],"17":[69],"days":[70],"post-sowing,":[71],"following":[72],"pre-defined":[74],"flight":[75,160],"path.":[76],"The":[77],"robust":[78],"estimation":[82],"process":[83],"incorporates":[84],"two":[85],"key":[86],"innovations:":[87],"first,":[88],"dynamic":[90],"system":[91],"of":[92,169,193,223],"12":[93],"adaptive":[94],"segmentation":[95],"thresholding":[96],"blocks":[97],"effectively":[99],"detects":[100],"seed":[102],"presence":[103],"across":[104],"diverse":[105],"variable":[107],"background":[108],"conditions.":[109],"Second,":[110],"tailored":[112],"three-layer":[113],"convolutional":[114],"neural":[115],"network":[116],"(CNN)":[117],"classifies":[119],"vegetative":[120],"situations.":[121],"To":[122],"maximize":[123],"the":[124,146,190,221],"training":[125],"efficiency":[126],"performance,":[128],"we":[129],"implemented":[130],"both":[131],"pretrained":[133],"model":[134],"deep":[137],"learning":[138],"model,":[139],"conducting":[140],"rigorous":[142],"comparative":[143],"analysis":[144],"against":[145],"state-of-the-art":[147],"YOLOv10.":[148],"Notably,":[149],"under":[150],"favorable":[151],"imaging":[152],"conditions,":[153],"findings":[155],"indicate":[156],"6-m":[159],"altitude":[161],"yields":[162],"optimal":[163],"results,":[164],"achieving":[165],"high":[167],"degree":[168],"accuracy":[170],"estimates":[175],"closely":[177],"align":[178],"those":[180],"obtained":[181],"through":[182],"ground-based":[184],"methods.":[185],"investigation":[187],"unequivocally":[188],"highlights":[189],"significant":[191],"advantages":[192],"UAV-based":[194],"monitoring":[195],"as":[196],"an":[197],"economically":[198],"viable,":[199],"comprehensive,":[201],"demonstrably":[203],"accurate":[204],"tool":[205],"for":[206],"precise":[207],"field":[209],"management,":[210],"ultimately":[211],"contributing":[212],"enhanced":[214],"crop":[215],"yields,":[216],"improved":[217],"food":[218],"security,":[219],"promotion":[222],"sustainable":[224],"agricultural":[225],"practices.":[226]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
