Plant Seedling Classification Using Preprocessed Deep CNN-Reference-Cited by-同舟云学术

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Plant Seedling Classification Using Preprocessed Deep CNN

Published:2023-03-03 Issue: Volume: Page:
ISSN:
Container-title:2023 15th International Conference on Computer and Automation Engineering (ICCAE)
language:
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Author:

Latif Ghazanfar¹,Mohammad Nazeeruddin²,Alghazo Jaafar³

Affiliation:

1. Prince Mohammad bin Fahd University,Computer Science Department,Al Khobar,Saudi Arabia

2. Prince Mohammad bin Fahd University,Cybersecurity Center,Al Khobar,Saudi Arabia

3. Virginia Military Institute,Department of Electrical and Computer Engineering,Lexington,VA,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10111091/10111098/10111357.pdf?arnumber=10111357

Reference23 articles.

1. AgroAVNET for crops and weeds classification: A step forward in automatic farming

2. Assessment of frost damage in mycorrhizal and non-mycorrhizal roots of Scots pine seedlings using classification analysis of their electrical impedance spectra

3. An Improved Deep Neural Network for Classification of Plant Seedling Images

4. Weed recognition by SVM texture feature classification in outdoor vegetable crops images

5. Study of digital image processing techniques for leaf disease detection and classification

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advancements in smart agriculture through innovative weed management using wavelet-based convolution neural network;Journal of High Speed Networks;2024-08-13

2. Automated design of Convolutional Neural Network architecture using Gray Wolf Optimization for plant seedlings classification;2024 8th International Conference on Image and Signal Processing and their Applications (ISPA);2024-04-21

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