{"id":"https://openalex.org/W3176480338","doi":"https://doi.org/10.1109/i2mtc50364.2021.9459976","title":"Deep learning techniques for enhancement of weeds growth classification","display_name":"Deep learning techniques for enhancement of weeds growth classification","publication_year":2021,"publication_date":"2021-05-17","ids":{"openalex":"https://openalex.org/W3176480338","doi":"https://doi.org/10.1109/i2mtc50364.2021.9459976","mag":"3176480338"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc50364.2021.9459976","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc50364.2021.9459976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061940144","display_name":"Dmitrii Vypirailenko","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Dmitrii Vypirailenko","raw_affiliation_strings":["Center for Computational and Data-Intensive Science and Engineering (CDISE),Moscow,Russia","Center for Computational and Data-Intensive Science and Engineering (CDISE), Moscow, Russia"],"affiliations":[{"raw_affiliation_string":"Center for Computational and Data-Intensive Science and Engineering (CDISE),Moscow,Russia","institution_ids":[]},{"raw_affiliation_string":"Center for Computational and Data-Intensive Science and Engineering (CDISE), Moscow, Russia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020078270","display_name":"Elizaveta Kiseleva","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elizaveta Kiseleva","raw_affiliation_strings":["Center for Computational and Data-Intensive Science and Engineering (CDISE),Moscow,Russia","Center for Computational and Data-Intensive Science and Engineering (CDISE), Moscow, Russia"],"affiliations":[{"raw_affiliation_string":"Center for Computational and Data-Intensive Science and Engineering (CDISE),Moscow,Russia","institution_ids":[]},{"raw_affiliation_string":"Center for Computational and Data-Intensive Science and Engineering (CDISE), Moscow, Russia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024830111","display_name":"Dmitrii Shadrin","orcid":"https://orcid.org/0000-0003-3486-8214"},"institutions":[{"id":"https://openalex.org/I125989756","display_name":"Skolkovo Institute of Science and Technology","ror":"https://ror.org/03f9nc143","country_code":"RU","type":"education","lineage":["https://openalex.org/I125989756"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Dmitrii Shadrin","raw_affiliation_strings":["Digital Agriculture Lab Skolkovo Institute of Science and Technology (SkolTech),Moscow,Russia","Digital Agriculture Lab Skolkovo Institute of Science and Technology (SkolTech), Moscow, Russia"],"affiliations":[{"raw_affiliation_string":"Digital Agriculture Lab Skolkovo Institute of Science and Technology (SkolTech),Moscow,Russia","institution_ids":["https://openalex.org/I125989756"]},{"raw_affiliation_string":"Digital Agriculture Lab Skolkovo Institute of Science and Technology (SkolTech), Moscow, Russia","institution_ids":["https://openalex.org/I125989756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067086380","display_name":"Mariia Pukalchik","orcid":"https://orcid.org/0000-0001-7996-642X"},"institutions":[{"id":"https://openalex.org/I125989756","display_name":"Skolkovo Institute of Science and Technology","ror":"https://ror.org/03f9nc143","country_code":"RU","type":"education","lineage":["https://openalex.org/I125989756"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Mariia Pukalchik","raw_affiliation_strings":["Digital Agriculture Lab Skolkovo Institute of Science and Technology (SkolTech),Moscow,Russia","Digital Agriculture Lab Skolkovo Institute of Science and Technology (SkolTech), Moscow, Russia"],"affiliations":[{"raw_affiliation_string":"Digital Agriculture Lab Skolkovo Institute of Science and Technology (SkolTech),Moscow,Russia","institution_ids":["https://openalex.org/I125989756"]},{"raw_affiliation_string":"Digital Agriculture Lab Skolkovo Institute of Science and Technology (SkolTech), Moscow, Russia","institution_ids":["https://openalex.org/I125989756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061940144"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3131,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.83128332,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9954000115394592,"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":0.9954000115394592,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9088000059127808,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12894","display_name":"Date Palm Research Studies","score":0.9072999954223633,"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/transfer-of-learning","display_name":"Transfer of learning","score":0.8109703063964844},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8074601888656616},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7439192533493042},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7133023142814636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6563717722892761},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6458033919334412},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6183866858482361},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.42781198024749756},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41351646184921265},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3458220958709717},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07097718119621277}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.8109703063964844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8074601888656616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7439192533493042},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7133023142814636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6563717722892761},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6458033919334412},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6183866858482361},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.42781198024749756},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41351646184921265},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3458220958709717},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07097718119621277},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/i2mtc50364.2021.9459976","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc50364.2021.9459976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1598866093","https://openalex.org/W1686810756","https://openalex.org/W1950580658","https://openalex.org/W1978813306","https://openalex.org/W2010934959","https://openalex.org/W2042013167","https://openalex.org/W2165698076","https://openalex.org/W2194775991","https://openalex.org/W2264784471","https://openalex.org/W2279098554","https://openalex.org/W2401231614","https://openalex.org/W2579348194","https://openalex.org/W2620742659","https://openalex.org/W2767106145","https://openalex.org/W2767767563","https://openalex.org/W2790979755","https://openalex.org/W2803513103","https://openalex.org/W2885735575","https://openalex.org/W2899268189","https://openalex.org/W2907735963","https://openalex.org/W2915645771","https://openalex.org/W2944014569","https://openalex.org/W2949079091","https://openalex.org/W2952651429","https://openalex.org/W2962782553","https://openalex.org/W2963446712","https://openalex.org/W2963754008","https://openalex.org/W2964121744","https://openalex.org/W2964137095","https://openalex.org/W3027329700","https://openalex.org/W3032628389"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W3183901164","https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W2951211570","https://openalex.org/W3192840557","https://openalex.org/W3103566983","https://openalex.org/W3135818718","https://openalex.org/W4290188444"],"abstract_inverted_index":{"Automatic":[0],"weed":[1,86,151],"control":[2,49],"is":[3,52],"becoming":[4],"a":[5],"popular":[6],"tool":[7],"for":[8,13,31,68,79,105,135,148],"agriculture":[9],"with":[10,145,202],"its":[11],"potential":[12],"boosting":[14],"crop":[15],"productivity.":[16],"Most":[17],"of":[18,39,183,204],"the":[19,35,43,74,100,115,141,157,168,196,207],"research":[20],"in":[21,45,166,181],"this":[22,70,137],"area":[23],"has":[24,160],"focused":[25],"on":[26],"developing":[27],"deep":[28,101,132],"learning":[29,76,96,106,133,209],"systems":[30],"weeds":[32],"recognition,":[33],"ignoring":[34],"possible":[36],"different":[37,150],"stages":[38],"their":[40,56,89],"growth.":[41],"In":[42,92],"meantime,":[44],"order":[46],"to":[47,54,84,98,190],"effectively":[48],"weeds,":[50],"it":[51],"useful":[53,107],"know":[55],"exact":[57],"species":[58],"and":[59,87,131,163,174,185,199],"growth":[60,90],"stage.":[61],"This":[62],"study":[63],"presents":[64],"another":[65],"effective":[66],"method":[67,159],"solving":[69,167],"problem.":[71,138],"We":[72,119,139,187],"use":[73],"transfer":[75,95,208],"approach":[77],"applied":[78],"Dense":[80],"Convolutional":[81],"Neural":[82],"Network":[83],"recognize":[85],"identify":[88],"stages.":[91],"our":[93,191],"work,":[94],"helps":[97],"pre-train":[99],"neural":[102,123],"network":[103],"model":[104],"features":[108],"such":[109],"as":[110],"leaf":[111],"characteristics":[112],"directly":[113],"from":[114],"input":[116],"data":[117,147],"representation.":[118],"explore":[120],"various":[121],"convolutional":[122],"networks":[124],"(ResNet,":[125],"MobileNet,":[126],"Wide":[127],"ResNet,":[128],"DenseNet)":[129],"architectures":[130],"approaches":[134],"addressing":[136],"used":[140],"publicly":[142],"available":[143],"dataset":[144],"labeled":[146],"18":[149],"species.":[152],"The":[153],"results":[154,165],"show":[155],"that":[156,194],"proposed":[158],"good":[161],"performance":[162],"better":[164],"classification":[169],"task":[170],"(71.81%":[171],"top1":[172],"accuracy":[173],"93.45%":[175],"top3":[176],"accuracy)":[177],"than":[178],"previous":[179],"methods":[180],"terms":[182],"memory":[184],"precision.":[186],"provide":[188],"access":[189],"code":[192],"[1]":[193],"includes":[195],"whole":[197],"pipeline":[198],"can":[200],"help":[201],"tasks":[203],"classification,":[205],"using":[206],"datasets.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}