{"id":"https://openalex.org/W4308146470","doi":"https://doi.org/10.1080/08839514.2022.2137642","title":"Yield-SpikeSegNet: An Extension of SpikeSegNet Deep-Learning Approach for the Yield Estimation in the Wheat Using Visual Images","display_name":"Yield-SpikeSegNet: An Extension of SpikeSegNet Deep-Learning Approach for the Yield Estimation in the Wheat Using Visual Images","publication_year":2022,"publication_date":"2022-10-30","ids":{"openalex":"https://openalex.org/W4308146470","doi":"https://doi.org/10.1080/08839514.2022.2137642"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2022.2137642","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2137642","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1080/08839514.2022.2137642","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041610999","display_name":"Tanuj Misra","orcid":"https://orcid.org/0000-0001-8096-0412"},"institutions":[{"id":"https://openalex.org/I1141210","display_name":"Indian Agricultural Statistics Research Institute","ror":"https://ror.org/03kkevc75","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1141210","https://openalex.org/I179420787"]},{"id":"https://openalex.org/I76253773","display_name":"Central Agricultural University","ror":"https://ror.org/03rs2w544","country_code":"IN","type":"education","lineage":["https://openalex.org/I76253773"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tanuj Misra","raw_affiliation_strings":["Department of Computer Science, Rani Lakshmi Bai Central Agricultural University, Jhansi, India","Division of Computer Applications, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Rani Lakshmi Bai Central Agricultural University, Jhansi, India","institution_ids":["https://openalex.org/I76253773"]},{"raw_affiliation_string":"Division of Computer Applications, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India","institution_ids":["https://openalex.org/I1141210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054714461","display_name":"Alka Arora","orcid":"https://orcid.org/0000-0003-0999-1077"},"institutions":[{"id":"https://openalex.org/I1141210","display_name":"Indian Agricultural Statistics Research Institute","ror":"https://ror.org/03kkevc75","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1141210","https://openalex.org/I179420787"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Alka Arora","raw_affiliation_strings":["Division of Computer Applications, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Computer Applications, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India","institution_ids":["https://openalex.org/I1141210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033799923","display_name":"Sudeep Marwaha","orcid":"https://orcid.org/0000-0002-5962-9757"},"institutions":[{"id":"https://openalex.org/I1141210","display_name":"Indian Agricultural Statistics Research Institute","ror":"https://ror.org/03kkevc75","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1141210","https://openalex.org/I179420787"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sudeep Marwaha","raw_affiliation_strings":["Division of Computer Applications, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Computer Applications, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India","institution_ids":["https://openalex.org/I1141210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064646117","display_name":"Ranjeet Ranjan Jha","orcid":"https://orcid.org/0000-0001-8406-5167"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ranjeet Ranjan Jha","raw_affiliation_strings":["School of Computing and Electrical Engineering (SCEE), Indian Institute of Technology Mandi, Mandi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Electrical Engineering (SCEE), Indian Institute of Technology Mandi, Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069687786","display_name":"Mrinmoy Ray","orcid":"https://orcid.org/0000-0002-1337-0348"},"institutions":[{"id":"https://openalex.org/I1141210","display_name":"Indian Agricultural Statistics Research Institute","ror":"https://ror.org/03kkevc75","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1141210","https://openalex.org/I179420787"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mrinmoy Ray","raw_affiliation_strings":["Division of Forecasting & Agricultural Systems Modeling, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Forecasting & Agricultural Systems Modeling, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India","institution_ids":["https://openalex.org/I1141210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100723761","display_name":"Shailendra Kumar","orcid":"https://orcid.org/0000-0002-5196-5027"},"institutions":[{"id":"https://openalex.org/I45509622","display_name":"Indian Agricultural Research Institute","ror":"https://ror.org/01bzgdw81","country_code":"IN","type":"facility","lineage":["https://openalex.org/I179420787","https://openalex.org/I45509622"]},{"id":"https://openalex.org/I76253773","display_name":"Central Agricultural University","ror":"https://ror.org/03rs2w544","country_code":"IN","type":"education","lineage":["https://openalex.org/I76253773"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shailendra Kumar","raw_affiliation_strings":["Department of Statistics, Rani Lakshmi Bai Central Agricultural University, Jhansi, India","Division of Plant Physiology, ICARR-Indian Agricultural Research Institute, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Rani Lakshmi Bai Central Agricultural University, Jhansi, India","institution_ids":["https://openalex.org/I76253773"]},{"raw_affiliation_string":"Division of Plant Physiology, ICARR-Indian Agricultural Research Institute, New Delhi, India","institution_ids":["https://openalex.org/I45509622"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000079748","display_name":"Sudhir Kumar","orcid":"https://orcid.org/0000-0002-1089-7435"},"institutions":[{"id":"https://openalex.org/I76253773","display_name":"Central Agricultural University","ror":"https://ror.org/03rs2w544","country_code":"IN","type":"education","lineage":["https://openalex.org/I76253773"]},{"id":"https://openalex.org/I45509622","display_name":"Indian Agricultural Research Institute","ror":"https://ror.org/01bzgdw81","country_code":"IN","type":"facility","lineage":["https://openalex.org/I179420787","https://openalex.org/I45509622"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sudhir Kumar","raw_affiliation_strings":["Department of Statistics, Rani Lakshmi Bai Central Agricultural University, Jhansi, India","Division of Plant Physiology, ICARR-Indian Agricultural Research Institute, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Rani Lakshmi Bai Central Agricultural University, Jhansi, India","institution_ids":["https://openalex.org/I76253773"]},{"raw_affiliation_string":"Division of Plant Physiology, ICARR-Indian Agricultural Research Institute, New Delhi, India","institution_ids":["https://openalex.org/I45509622"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004149609","display_name":"Viswanathan Chinnusamy","orcid":"https://orcid.org/0000-0003-2174-9064"},"institutions":[{"id":"https://openalex.org/I45509622","display_name":"Indian Agricultural Research Institute","ror":"https://ror.org/01bzgdw81","country_code":"IN","type":"facility","lineage":["https://openalex.org/I179420787","https://openalex.org/I45509622"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Viswanathan Chinnusamy","raw_affiliation_strings":["Division of Plant Physiology, ICARR-Indian Agricultural Research Institute, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Plant Physiology, ICARR-Indian Agricultural Research Institute, New Delhi, India","institution_ids":["https://openalex.org/I45509622"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5054714461"],"corresponding_institution_ids":["https://openalex.org/I1141210"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":2.3105,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.88308517,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"36","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9993000030517578,"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":0.9993000030517578,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.994700014591217,"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":0.9904000163078308,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7823725938796997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6590786576271057},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.6117790937423706},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6039324998855591},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.595715343952179},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5698479413986206},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.5176159143447876},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5084964036941528},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5021107196807861},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46349048614501953},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37466180324554443}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7823725938796997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6590786576271057},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.6117790937423706},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6039324998855591},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.595715343952179},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5698479413986206},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.5176159143447876},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5084964036941528},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5021107196807861},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46349048614501953},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37466180324554443},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2022.2137642","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2137642","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fc34145670a54e52b238247599032998","is_oa":false,"landing_page_url":"https://doaj.org/article/fc34145670a54e52b238247599032998","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 36, Iss 1 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/08839514.2022.2137642","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2137642","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W195150910","https://openalex.org/W1693171120","https://openalex.org/W1901129140","https://openalex.org/W1968060974","https://openalex.org/W2000563201","https://openalex.org/W2013414890","https://openalex.org/W2017101219","https://openalex.org/W2127293692","https://openalex.org/W2157150618","https://openalex.org/W2541344361","https://openalex.org/W2559655401","https://openalex.org/W2743389070","https://openalex.org/W2761162227","https://openalex.org/W2767103329","https://openalex.org/W2767126550","https://openalex.org/W2783264619","https://openalex.org/W2966523470","https://openalex.org/W3003996330","https://openalex.org/W3009441850","https://openalex.org/W3012947883","https://openalex.org/W3129635925"],"related_works":["https://openalex.org/W2174331923","https://openalex.org/W2050175337","https://openalex.org/W2769135912","https://openalex.org/W2329992713","https://openalex.org/W3050304047","https://openalex.org/W2062974934","https://openalex.org/W2317338006","https://openalex.org/W2385487847","https://openalex.org/W2385476654","https://openalex.org/W2904960904"],"abstract_inverted_index":{"High-throughput":[0],"plant":[1,18,36,69],"phenotyping":[2],"integrated":[3],"with":[4],"computer":[5],"vision":[6],"is":[7,91,106,167],"an":[8],"emerging":[9,23],"topic":[10],"in":[11,33,43,66,133,146,172],"the":[12,22,27,34,63,67,130,134,164,173],"domain":[13,174],"of":[14,21,41,76,103,175],"nondestructive":[15,45,178],"and":[16,26,83,101,109,125,141,152,158,177],"noninvasive":[17],"breeding.":[19],"Analysis":[20],"grain":[24,28],"spikes":[25],"weight":[29],"or":[30],"yield":[31,64,113,131,159],"estimation":[32,65,85,114,132,160],"wheat":[35,68,135,179],"for":[37,62,98,129],"a":[38,44,57,94,168],"huge":[39],"number":[40],"genotypes":[42],"way":[46],"has":[47],"achieved":[48],"significant":[49,169],"research":[50],"attention.":[51],"In":[52,112],"this":[53,104],"study,":[54],"we":[55,116],"developed":[56],"deep":[58,95],"learning":[59,119],"approach,":[60],"\u201cYield-SpikeSegNet,\u201d":[61],"using":[70,93,121],"visual":[71],"images.":[72],"Our":[73],"approach":[74,166],"consists":[75],"two":[77],"consecutive":[78],"modules:":[79],"\u201cSpike":[80],"detection":[81,89],"module\u201d":[82],"\u201cYield":[84],"module.\u201d":[86],"The":[87,137,155],"spike":[88,99,107,110,147,156],"module":[90,105],"implemented":[92],"encoder-decoder":[96],"network":[97,124],"segmentation":[100,148,157],"output":[102],"area":[108],"count.":[111],"module,":[115],"develop":[117],"machine":[118],"models":[120],"artificial":[122],"neural":[123],"support":[126],"vector":[127],"regression":[128],"plant.":[136],"model\u2019s":[138],"precision,":[139],"accuracy,":[140],"robustness":[142],"are":[143],"found":[144],"satisfactory":[145],"as":[149],"0.9982,":[150],"0.9987,":[151],"0.9992,":[153],"respectively.":[154],"performance":[161],"reflect":[162],"that":[163],"Yield-SpikeSegNet":[165],"step":[170],"forward":[171],"high-throughput":[176],"phenotyping.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
