{"id":"https://openalex.org/W3175889036","doi":"https://doi.org/10.1109/i2mtc50364.2021.9459943","title":"Deep Learning Approach for high Energy efficient Real-Time Detection of Weeds in Organic Farming","display_name":"Deep Learning Approach for high Energy efficient Real-Time Detection of Weeds in Organic Farming","publication_year":2021,"publication_date":"2021-05-17","ids":{"openalex":"https://openalex.org/W3175889036","doi":"https://doi.org/10.1109/i2mtc50364.2021.9459943","mag":"3175889036"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc50364.2021.9459943","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc50364.2021.9459943","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/A5014725084","display_name":"Vitali Czymmek","orcid":"https://orcid.org/0000-0001-5981-0735"},"institutions":[{"id":"https://openalex.org/I4210131906","display_name":"West Coast University of Applied Sciences","ror":"https://ror.org/03bthq143","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210131906"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Vitali Czymmek","raw_affiliation_strings":["Faculty of Engineering, West Coast University of Applied Sciences, Heide, Germany"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, West Coast University of Applied Sciences, Heide, Germany","institution_ids":["https://openalex.org/I4210131906"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078327498","display_name":"Clarissa M\u00f6ller","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131906","display_name":"West Coast University of Applied Sciences","ror":"https://ror.org/03bthq143","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210131906"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Clarissa Moller","raw_affiliation_strings":["Faculty of Engineering, West Coast University of Applied Sciences, Heide, Germany"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, West Coast University of Applied Sciences, Heide, Germany","institution_ids":["https://openalex.org/I4210131906"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043913938","display_name":"Leif O. Harders","orcid":"https://orcid.org/0000-0003-3121-9438"},"institutions":[{"id":"https://openalex.org/I4210131906","display_name":"West Coast University of Applied Sciences","ror":"https://ror.org/03bthq143","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210131906"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Leif O. Harders","raw_affiliation_strings":["Faculty of Engineering, West Coast University of Applied Sciences, Heide, Germany"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, West Coast University of Applied Sciences, Heide, Germany","institution_ids":["https://openalex.org/I4210131906"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001586663","display_name":"Stephan Hu\u00dfmann","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131906","display_name":"West Coast University of Applied Sciences","ror":"https://ror.org/03bthq143","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210131906"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stephan Hussmann","raw_affiliation_strings":["Faculty of Engineering, West Coast University of Applied Sciences, Heide, Germany"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, West Coast University of Applied Sciences, Heide, Germany","institution_ids":["https://openalex.org/I4210131906"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014725084"],"corresponding_institution_ids":["https://openalex.org/I4210131906"],"apc_list":null,"apc_paid":null,"fwci":1.9696,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.86764288,"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":0.9976000189781189,"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":0.9976000189781189,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9812999963760376,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer 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":0.7006416320800781},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.531787633895874},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5088801383972168},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5057268142700195},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.47483187913894653},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46590715646743774},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.45158132910728455},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.43755218386650085},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.42528748512268066},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4161854684352875},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.41265174746513367},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3324534595012665},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13733336329460144},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.114845871925354},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.09082528948783875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7006416320800781},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.531787633895874},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5088801383972168},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5057268142700195},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.47483187913894653},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46590715646743774},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.45158132910728455},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.43755218386650085},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.42528748512268066},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4161854684352875},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.41265174746513367},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3324534595012665},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13733336329460144},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.114845871925354},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.09082528948783875},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/i2mtc50364.2021.9459943","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc50364.2021.9459943","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":[{"score":0.8799999952316284,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W88752840","https://openalex.org/W1043519844","https://openalex.org/W2003660891","https://openalex.org/W2031489346","https://openalex.org/W2039970331","https://openalex.org/W2044651338","https://openalex.org/W2051666323","https://openalex.org/W2054866485","https://openalex.org/W2069747077","https://openalex.org/W2087082746","https://openalex.org/W2120082031","https://openalex.org/W2124290272","https://openalex.org/W2125286842","https://openalex.org/W2127229650","https://openalex.org/W2129440600","https://openalex.org/W2141277076","https://openalex.org/W2152525636","https://openalex.org/W2155669845","https://openalex.org/W2243003515","https://openalex.org/W2333820999","https://openalex.org/W2394911398","https://openalex.org/W2606722458","https://openalex.org/W2966061439","https://openalex.org/W2987175876","https://openalex.org/W2998564420","https://openalex.org/W3047986474","https://openalex.org/W3106250896","https://openalex.org/W3187740239","https://openalex.org/W4297775537","https://openalex.org/W6603545793","https://openalex.org/W6798675566"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W179829755","https://openalex.org/W3143109941"],"abstract_inverted_index":{"Organic":[0],"farming,":[1],"vision":[2],"based":[3],"detection":[4],"and":[5,14,61,75,142],"classification":[6,24],"systems":[7],"can":[8,105],"be":[9,48],"used":[10],"to":[11,23,54,95,113,126],"reduce":[12],"chemical":[13],"synthetic":[15],"pesticides.":[16],"Automated":[17],"weeding":[18],"control":[19],"requires":[20],"in":[21],"addition":[22],"also":[25],"localization":[26],"through":[27],"bounding":[28],"boxes.":[29],"By":[30],"using":[31],"tensor":[32,103],"processing":[33],"units,":[34],"the":[35,135,138,143,150,156],"typical":[36],"implementation":[37],"of":[38,44,92,102,111,120,137,158],"convolutional":[39],"neural":[40],"networks":[41],"by":[42],"means":[43],"graphics":[45],"cards":[46],"should":[47],"improved.":[49],"The":[50,84,100],"main":[51],"objective":[52],"is":[53,82,115,123,140,146],"improve":[55],"energy":[56,144],"consumption":[57],"without":[58],"deteriorating":[59],"accuracy":[60,110,157],"frame":[62],"rate.":[63],"In":[64,148],"this":[65,89],"approach":[66],"a":[67,76,127,132,159,164],"Google":[68],"Coral":[69],"USB":[70],"Accelerator":[71],"with":[72],"an":[73],"Edge-TPU":[74],"Raspberry":[77],"PI":[78],"4":[79],"Model":[80],"B":[81],"used.":[83],"MobileNetV2-SSD":[85],"was":[86,167],"chosen":[87],"for":[88],"application":[90],"because":[91],"its":[93],"ability":[94],"run":[96],"on":[97,131,163],"embedded":[98],"systems.":[99],"use":[101],"processors":[104],"enable":[106],"time-saving":[107],"calculations.":[108],"An":[109],"up":[112],"62.3%":[114],"achieved.":[116,169],"A":[117],"maximum":[118],"power":[119],"5.7":[121],"W":[122],"obtained.":[124],"Compared":[125],"tiny-YOLO":[128,160],"network":[129,161],"accelerated":[130,162],"Jetson":[133,165],"TX2,":[134],"speed":[136],"CNN":[139],"outperformed":[141],"efficiency":[145],"increased.":[147],"addition,":[149],"acquisition":[151],"costs":[152],"are":[153],"lower.":[154],"Nevertheless,":[155],"TX2":[166],"not":[168]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}