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dc.title | Scouting of whiteflies in tomato greenhouse environment using deep learning | en |
dc.contributor.author | Tureček, Tomáš | |
dc.contributor.author | Vařacha, Pavel | |
dc.contributor.author | Turečková, Alžběta | |
dc.contributor.author | Psota, Václav | |
dc.contributor.author | Janků, Peter | |
dc.contributor.author | Štěpánek, Vít | |
dc.contributor.author | Viktorin, Adam | |
dc.contributor.author | Šenkeřík, Roman | |
dc.contributor.author | Jašek, Roman | |
dc.contributor.author | Chramcov, Bronislav | |
dc.contributor.author | Grivas, Ioannis | |
dc.contributor.author | Komínková Oplatková, Zuzana | |
dc.relation.ispartof | Smart Innovation, Systems and Technologies | |
dc.identifier.issn | 2190-3018 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.identifier.isbn | 978-981-16-3348-5 | |
dc.date.issued | 2022 | |
utb.relation.volume | 245 | |
dc.citation.spage | 323 | |
dc.citation.epage | 335 | |
dc.event.title | 1st International Conference on Agriculture Digitalization and Organic Production, ADOP 2021 | |
dc.event.location | St. Petersburg | |
utb.event.state-en | Russia | |
utb.event.state-cs | Rusko | |
dc.event.sdate | 2021-06-07 | |
dc.event.edate | 2021-06-09 | |
dc.type | conferenceObject | |
dc.language.iso | en | |
dc.publisher | Springer Science and Business Media Deutschland GmbH | |
dc.identifier.doi | 10.1007/978-981-16-3349-2_27 | |
dc.relation.uri | https://link.springer.com/chapter/10.1007/978-981-16-3349-2_27 | |
dc.subject | automated counting | en |
dc.subject | convolutional neural network | en |
dc.subject | deep transfer learning | en |
dc.subject | faster R-CNN | en |
dc.subject | tomato greenhouse | en |
dc.subject | whiteflies scouting | en |
dc.description.abstract | This study shows the possibilities of how to replace tedious human labor—scouting of yellow sticky traps (YST) for whiteflies—using artificial cognitive vision, specifically the deep convolutional network (CNN), as a part of the more complex system—BERABOT. The used CNN is the Faster R-CNN trained by deep transfer learning to substitute human scouting when the low whiteflies infection phase was specifically targeted. The training was conducted on pictures taken inside the heated and lighted tomato production greenhouse of “Bezdínek Farm” in Dolni Lutyne, Czechia. Used pictures were collected in a way planned for future fully automated robotic applications in the BERABOT system. The achieved results were compared with the scouting results of a professional phytopathologist. The trained employee’s scouting results against the professional phytopathologist accomplished root-mean-square error (RMSE) equal to 4.23, while the developed CNN model was evaluated to be 5.83. The results presented here open up new frontiers for further CNN model tuning leading to the potential in substituting an employee(s) in the future and make tomato production less expensive and less human labor dependent. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1010583 | |
utb.identifier.obdid | 43883183 | |
utb.identifier.scopus | 2-s2.0-85115131306 | |
utb.source | d-scopus | |
dc.date.accessioned | 2021-10-08T21:13:50Z | |
dc.date.available | 2021-10-08T21:13:50Z | |
dc.description.sponsorship | IGA/CebiaTech/2021/001; Technology Agency of the Czech Republic, TACR: FW01010381 | |
utb.contributor.internalauthor | Tureček, Tomáš | |
utb.contributor.internalauthor | Vařacha, Pavel | |
utb.contributor.internalauthor | Turečková, Alžběta | |
utb.contributor.internalauthor | Janků, Peter | |
utb.contributor.internalauthor | Viktorin, Adam | |
utb.contributor.internalauthor | Šenkeřík, Roman | |
utb.contributor.internalauthor | Jašek, Roman | |
utb.contributor.internalauthor | Chramcov, Bronislav | |
utb.contributor.internalauthor | Komínková Oplatková, Zuzana | |
utb.fulltext.affiliation | 1 Tomáš Tureček, Pavel Vařacha, Alžběta Turečková, Peter Janků, Adam Viktorin, Roman Šenkeřík, Roman Jašek, Bronislav Chramcov, Zuzana Komínková Oplatková 2 Václav Psota, Vít Štěpánek 3 Ioannis Grivas 1 Tomas Bata University in Zlín, nám. T. G. Masaryka 5555, 760 01 Zlín, Czechia {tturecek, varacha, tureckova, janku, viktorin, senkerik, jasek, chramcov, oplatkova}@utb.cz | http://www.utb.cz 2 NWT a.s., třída Tomáše Bati 269, 760 01 Zlín, Czechia {vaclav.psota,vit.stepanek}@nwt.cz | http://www.nwt.cz 3 University of Thessaly General Department (Lamia), Greece igrivas1@uth.gr | |
utb.fulltext.dates | - | |
utb.fulltext.sponsorship | This work is supported by the Technology Agency of the Czech Republic under the TREND Programme, project No. FW01010381, resources of A.I.Lab (ailab.fai.utb.cz) at the Faculty of Applied Informatics, Tomas Bata University in Zlin (TBU), and by Internal Grant Agency of TBU under the project no. IGA/CebiaTech/2021/001. | |
utb.scopus.affiliation | Tomas Bata University in Zlín, nám. T. G. Masaryka 5555, Zlín, 760 01, Czech Republic; NWT a.s., třída Tomáše Bati 269, Zlín, 760 01, Czech Republic; General Department (Lamia), University of Thessaly, Volos, Greece | |
utb.fulltext.projects | FW01010381 | |
utb.fulltext.projects | IGA/CebiaTech/2021/001 | |
utb.fulltext.faculty | - | |
utb.fulltext.ou | - |