A Comparative Study on the Modern Deep Learning Architectures For Predicting Nutritional Deficiency in Rice Plants-Reference-Cited by-同舟云学术

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A Comparative Study on the Modern Deep Learning Architectures For Predicting Nutritional Deficiency in Rice Plants

Published:2023-05-19 Issue: Volume: Page:
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Container-title:2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET)
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Author:

Senjaliya Harsh¹,Gajjar Pranshav²,Dodia Virensinh²,Shah Pooja³,Bardhan Kirti⁴,Shukla Madhu⁵

Affiliation:

1. Uka Tarsadia University,Department of Mechatronics

2. Nirma University,Institute of Technology

3. PDEU,School of Technology

4. Navsari Agricultural University,Department of Basic Sciences and Humanities

5. Marwadi University,Department of Computer Engineering

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10149892/10149896/10149936.pdf?arnumber=10149936

Reference33 articles.

1. Recent advances and applications of deep learning methods in materials science

2. Deep learning in optical metrology: a review

Cited by 1 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. PND-Net: plant nutrition deficiency and disease classification using graph convolutional network;Scientific Reports;2024-07-05

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