Combining Spatial and Temporal Analysis: A CNN-LSTM Hybrid Model for Maize Disease Classification-Reference-Cited by-同舟云学术

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Combining Spatial and Temporal Analysis: A CNN-LSTM Hybrid Model for Maize Disease Classification

Published:2024-02-09 Issue: Volume: Page:1529-1533
ISSN:
Container-title:2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT)
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Author:

Thapliyal Nitin¹,Aeri Manisha¹,Kumar Abhishek²,Kukreja Vinay³,Sharma Rishabh³

Affiliation:

1. Graphic Era Hill University,Computer Science and Engineering,Dehradun,Uttrakhand,India

2. Computer Science and Engineering (Artificial Intelligence) IIMT College of Engineering,Greater Noida,UP,India

3. Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10486056/10486063/10486456.pdf?arnumber=10486456

Reference17 articles.

1. Machine Learning and Deep Learning for Smart Agriculture and Applications;Hashmi;IGI Global,2023

2. Prediction of Maize Leaf Disease Detection to improve Crop Yield using Machine Learning based Models

3. Maize leaf disease classification using deep convolutional neural networks

4. Northern Maize Leaf Blight Detection Under Complex Field Environment Based on Deep Learning

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1. Employee Attrition Analysis Using XGBoost;2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE);2024-05-09

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