An Intelligent Plant Dissease Detection System for Smart Hydroponic Using Convolutional Neural Network-Reference-Cited by-同舟云学术

An Intelligent Plant Dissease Detection System for Smart Hydroponic Using Convolutional Neural Network

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 14th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)
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Author:

Musa Aminu¹,Hamada Mohamed²,Aliyu Farouq Muhammad³,Hassan Mohammed⁴

Affiliation:

1. Federal University Dutse,Department of Computer Science,Dutse,Nigeria

2. University of Aizu,Software Eng. Lab,Aizu,Japan

3. Yobe state University,Department of Computer Science,Damaturu,Nigeria

4. Bayero University Kano,Department of Software Eng.,Kano,Nigeria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9691770/9691932/09691971.pdf?arnumber=9691971

Reference33 articles.

1. Plant disease detection using image processing and machine learning;kulkarni;ArXiv Preprint,2021

2. Jmage based plant disease detection in pomegranate plant for bacterial blight;sharath;2019 International Conference on Communication and Signal Processing (ICCSP) JEEE,0

3. Jntegrating soms and a bayesian classifier for segmenting diseased plants in uncontrolled environments;hernández-rabadán;The Scientific World Journal,2014

4. Performance Evaluation of Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF)

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