Small CNN for Plant Disease Classification Using Quantization-Aware Training: A Case Study on MobileNetV3-Reference-Cited by-同舟云学术

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Small CNN for Plant Disease Classification Using Quantization-Aware Training: A Case Study on MobileNetV3

Published:2023-11-15 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)
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Author:

Syaharani Aulia Bunga¹,Sulandari Winita¹,Pardede Hilman F.²,Heryana Ana²,Suryawati Endang²,Subekti Agus³

Affiliation:

1. Universitas Sebelas Maret,Department of Statistics,Surakarta,Indonesia

2. National Research and Innovation Agency (BRIN),Research Center for Artificial Intelligence and Cybersecurity,Bandung,Indonesia

3. National Research and Innovation Agency (BRIN),Research Center for Telecommunications,Bandung,Indonesia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10366459/10366464/10366600.pdf?arnumber=10366600

Reference23 articles.

1. Automatic plant pest detection and recognition using k-means clustering algorithm and correspondence filters;Faithpraise;International Journal of Advanced Biotechnology and Research,2013

2. Vision-based pest detection based on SVM classification method

3. Image-based disease diagnosing and predicting of the crops through the deep learning mechanism

4. Plant Disease Classification Using Image Segmentation and SVM Techniques;Elangovan;International Journal of Computational Intelligence Research,2017

5. Identification of Apple Leaf Diseases Based on Deep Convolutional Neural Networks

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