{"id":"https://openalex.org/W4312721400","doi":"https://doi.org/10.1109/access.2022.3230355","title":"Study on Deep Learning Model for Online Estimation of Chlorophyll Content Based on Near Ground Multispectral Feature Bands","display_name":"Study on Deep Learning Model for Online Estimation of Chlorophyll Content Based on Near Ground Multispectral Feature Bands","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312721400","doi":"https://doi.org/10.1109/access.2022.3230355"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3230355","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3230355","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09991996.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09991996.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103060548","display_name":"Jiaxing Gao","orcid":"https://orcid.org/0000-0001-7764-5542"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaxing Gao","raw_affiliation_strings":["Key Laboratory of Wireless Networks and Mobile Computing, School of Computer Science, Inner Mongolia University, Hohhot, China","School of Computer Science, Key Laboratory of Wireless Networks and Mobile Computing, Inner Mongolia University, Hohhot, China","School of Computer science, Inner Mongolia University, Hohhot, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Wireless Networks and Mobile Computing, School of Computer Science, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"School of Computer Science, Key Laboratory of Wireless Networks and Mobile Computing, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"School of Computer science, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081014401","display_name":"Zhibin Zhang","orcid":"https://orcid.org/0000-0002-7754-0385"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibin Zhang","raw_affiliation_strings":["Key Laboratory of Wireless Networks and Mobile Computing, School of Computer Science, Inner Mongolia University, Hohhot, China","School of Computer Science, Key Laboratory of Wireless Networks and Mobile Computing, Inner Mongolia University, Hohhot, China","School of Computer science, Inner Mongolia University, Hohhot, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Wireless Networks and Mobile Computing, School of Computer Science, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"School of Computer Science, Key Laboratory of Wireless Networks and Mobile Computing, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]},{"raw_affiliation_string":"School of Computer science, Inner Mongolia University, Hohhot, China","institution_ids":["https://openalex.org/I2722730"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103060548"],"corresponding_institution_ids":["https://openalex.org/I2722730"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.9107,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.7037858,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"10","issue":null,"first_page":"132183","last_page":"132192"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9988999962806702,"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"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9957000017166138,"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":0.9944999814033508,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.844302237033844},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7144593596458435},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6311112642288208},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6295782327651978},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6124844551086426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5712577104568481},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5489925146102905},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5231952667236328},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4740604758262634},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4628855884075165},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41897016763687134},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.41140782833099365},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23807206749916077},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11319926381111145},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10740071535110474}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.844302237033844},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7144593596458435},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6311112642288208},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6295782327651978},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6124844551086426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5712577104568481},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5489925146102905},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5231952667236328},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4740604758262634},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4628855884075165},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41897016763687134},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.41140782833099365},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23807206749916077},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11319926381111145},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10740071535110474},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":2,"locations":[{"id":"doi:10.1109/access.2022.3230355","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3230355","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09991996.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2e830a62d1ff49998baf030550bbeaf6","is_oa":true,"landing_page_url":"https://doaj.org/article/2e830a62d1ff49998baf030550bbeaf6","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":"IEEE Access, Vol 10, Pp 132183-132192 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3230355","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3230355","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09991996.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G589198052","display_name":null,"funder_award_id":"2021SZD0026","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7128713766","display_name":null,"funder_award_id":"31760345","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312721400.pdf","grobid_xml":"https://content.openalex.org/works/W4312721400.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1924770834","https://openalex.org/W1982755765","https://openalex.org/W2064636932","https://openalex.org/W2118026371","https://openalex.org/W2207086047","https://openalex.org/W2319109428","https://openalex.org/W2342274513","https://openalex.org/W2715659545","https://openalex.org/W2770928509","https://openalex.org/W2796330417","https://openalex.org/W2799624479","https://openalex.org/W2889764476","https://openalex.org/W2892218474","https://openalex.org/W2900875525","https://openalex.org/W2945222626","https://openalex.org/W2980620471","https://openalex.org/W2989880742","https://openalex.org/W2990291058","https://openalex.org/W3011149747","https://openalex.org/W3020020118","https://openalex.org/W3060826539","https://openalex.org/W3084417673","https://openalex.org/W3095502701","https://openalex.org/W3122716237","https://openalex.org/W3128822263","https://openalex.org/W3134781677","https://openalex.org/W3198904966","https://openalex.org/W3201188184","https://openalex.org/W3203632185","https://openalex.org/W4206334812","https://openalex.org/W6640212811","https://openalex.org/W6687991213","https://openalex.org/W6732006753","https://openalex.org/W6770641310"],"related_works":["https://openalex.org/W4318664220","https://openalex.org/W2771047279","https://openalex.org/W4388409104","https://openalex.org/W2124951708","https://openalex.org/W1544811710","https://openalex.org/W172072032","https://openalex.org/W2006066416","https://openalex.org/W3157073418","https://openalex.org/W4372048956","https://openalex.org/W1980222719"],"abstract_inverted_index":{"Chlorophyll":[0],"content":[1,24,70,195],"of":[2,9,21,25,67,71,99,155,158,166,169,196],"plant":[3],"leaves":[4],"is":[5,15,86,178],"an":[6,153,164],"essential":[7],"indicator":[8],"crop":[10],"growth":[11],"status.":[12],"This":[13],"study":[14],"focused":[16],"on":[17,127,160,171,203],"the":[18,22,58,68,78,91,95,103,110,118,123,131,138,175,182],"nondestructive":[19],"estimation":[20],"chlorophyll":[23,69,194],"maize":[26,72,200],"using":[27,122],"near":[28,204],"ground":[29,205],"multispectral":[30,75,206],"data.":[31],"We":[32],"propose":[33],"a":[34,46,188],"one-dimensional":[35],"convolutional":[36],"neural":[37,63],"network-gated":[38],"recurrent":[39,60],"unit":[40,61],"(1-D-CNN-GRU).":[41],"That":[42],"is,":[43],"it":[44],"combines":[45],"1D-CNN":[47],"with":[48,57,152],"strong":[49,54],"feature":[50,92,112,129],"expression":[51],"capacity":[52,56],"and":[53,148,163],"memory":[55],"gated":[59],"(GRU)":[62],"network":[64],"to":[65,89],"estimate":[66],"directly":[73],"from":[74,94],"images.":[76],"Furthermore,":[77],"iteratively":[79],"retaining":[80],"informative":[81],"variables-successive":[82],"projections":[83],"algorithm":[84],"(IRIV-SPA)":[85],"first":[87],"used":[88],"select":[90],"wavebands":[93,98,113,120],"11":[96],"available":[97],"two":[100],"datasets":[101],"in":[102,181],"experiment.":[104,183],"The":[105],"experimental":[106],"results":[107],"show":[108],"that":[109],"selected":[111],"have":[114],"more":[115],"accuracy":[116],"than":[117,137],"raw":[119],"when":[121],"same":[124],"model;":[125],"based":[126,202],"these":[128],"wavebands,":[130],"1D-CNN-GRU":[132],"model":[133],"has":[134],"smaller":[135],"errors":[136],"other":[139],"conventional":[140],"models":[141],"such":[142,198],"as":[143,199],"support":[144],"vector":[145],"regression":[146],"(SVR)":[147],"random":[149],"forest":[150],"(RF),":[151],"MRE":[154,165],"0.069,":[156],"RMSE":[157,168],"3.473":[159],"Datasets":[161,172],"I,":[162],"0.108,":[167],"7.568":[170],"II.":[173],"Meanwhile,":[174],"real-time":[176],"performance":[177],"also":[179],"validated":[180],"These":[184],"investigations":[185],"can":[186],"provide":[187],"valuable":[189],"guidance":[190],"for":[191,210],"online":[192],"monitoring":[193],"crops":[197],"etc.,":[201],"band":[207],"data":[208],"processing":[209],"developing":[211],"smart":[212],"agricultural":[213],"system.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}