Unsupervised Convolutional Autoencoder-Based Feature Learning for Automatic Detection of Plant Diseases

Developing an automatic detector of plant diseases is one of application fields in machine learning. Ground-truth diagnoses of plant diseases which are conducted by experts in laboratory tests are often inapplicable for fast and cheap implementations. Using machine learning approaches, the images of...

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Veröffentlicht in:	2018 International Conference on Computer, Control, Informatics and Its Applications (IC3INA) S. 158 - 162
Hauptverfasser:	Pardede, Hilman F., Suryawati, Endang, Sustika, Rika, Zilvan, Vicky
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.11.2018
Schlagworte:	convolutional autoen-coder Deep learning Diseases Feature extraction feature learning Kernel Plant diseases detection Support vector machines SVM Training
Online-Zugang:	Volltext
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