Plant Disease Prognosis Using Spatial-Exploitation-Based Deep-Learning Models-Reference-Cited by-同舟云学术

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Plant Disease Prognosis Using Spatial-Exploitation-Based Deep-Learning Models

Published:2023-12-21 Issue: Volume:167 Page:137
ISSN:
Container-title:RAiSE-2023
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Author:

Vankara Jayavani¹^ORCID,Nandini Sekharamahanti S.¹,Muddada Murali Krishna¹^ORCID,Kuppili N. Satya Chitra²,Naidu K Sowjanya³

Affiliation:

1. Department of Computer Science and Engineering, GITAM School of Technology GITAM (Deemed to Be University), Visakhapatnam 500020, India

2. Department of Computer Science and Engineering, Dr. Lankapalli Bullayya College of Engineering, Visakhapatnam 500020, India

3. Department of CSE-IoT, Malla Reddy Engineering College(A), Malkajgiri 500015, India

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/59/1/137/pdf

Reference20 articles.

1. Crop conditional Convolutional Neural Networks for massive multi-crop plant disease classification over cell phone acquired images taken on real field conditions;Picon;Comput. Electron. Agric.,2019

2. Plant species identification from occluded leaf images;Chaudhury;IEEE/ACM Trans. Comput. Biol. Bioinform.,2018

3. Real-time detection of maize crop disease via a deep learning-based smartphone app;Richey;Real-Time Image Processing and Deep Learning,2020

4. Glomerular disease classification and lesion identification by machine learning;Yang;Biomed. J.,2022

5. Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges;Shrestha;J. Bus. Res.,2021

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