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Detekcija bolesti biljaka tehnikama dubokog učenja

Plant disease detections using deep learning techniques

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2020
Disertacija.pdf (5.356Mb)
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Author
Arsenović, Marko
Mentor
Sladojević, Srđan
Committee members
Stefanović, Darko
Anderla, Andraš
Ivanišević, Dragoslav
Rakić, Aleksandar
Sladojević, Srđan
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Abstract
Istraživanja predstavljena u disertaciji imala su za cilj razvoj nove metode bazirane na dubokim konvolucijskim neuoronskim mrežama u cilju detekcije bolesti biljaka na osnovu slike lista. U okviru eksperimentalnog dela rada prikazani su dosadašnji literaturno dostupni pristupi u automatskoj detekciji bolesti biljaka kao i ograničenja ovako dobijenih modela kada se koriste u prirodnim uslovima. U okviru disertacije uvedena je nova baza slika listova, trenutno najveća po broju slika u poređenju sa javno dostupnim bazama, potvrđeni su novi pristupi augmentacije bazirani na GAN arhitekturi nad slikama listova uz novi specijalizovani dvo-koračni pristup kao potencijalni odgovor na nedostatke postojećih rešenja.
The research presented in this thesis was aimed at developing a novel method based on deep convolutional neural networks for automated plant disease detection. Based on current available literature, specialized two-phased deep neural network method introduced in the experimental part of thesis solves the limitations of state-of-the-art plant disease detection methods and provides the possibility for a practical usage of the newly developed model. In addition, a new dataset was introduced, that has more images of leaves than other publicly available datasets, also GAN based augmentation approach on leaves images is experimentally confirmed.
Faculty:
University of Novi Sad, Faculty of Technical Science
Date:
07-10-2020
Keywords:
Duboko učenje, konovolucijske neuronske mreže, klasifikacija, detekcija objekata / Deep learning, convolutional neural networks, classification, object detection
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https://www.cris.uns.ac.rs/DownloadFileServlet/Disertacija159437067647076.pdf?controlNumber=(BISIS)114816&fileName=159437067647076.pdf&id=16035&source=NaRDuS&language=sr
https://www.cris.uns.ac.rs/record.jsf?recordId=114816&source=NaRDuS&language=sr
https://www.cris.uns.ac.rs/DownloadFileServlet/IzvestajKomisije159437068315281.pdf?controlNumber=(BISIS)114816&fileName=159437068315281.pdf&id=16036&source=NaRDuS&language=sr
/DownloadFileServlet/IzvestajKomisije159437068315281.pdf?controlNumber=(BISIS)114816&fileName=159437068315281.pdf&id=16036
https://nardus.mpn.gov.rs/handle/123456789/17974

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