Efficient Disease Detection in Wheat Crops: A Hybrid Deep Learning Solution-Reference-Cited by-同舟云学术

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Efficient Disease Detection in Wheat Crops: A Hybrid Deep Learning Solution

Published:2023-11-01 Issue: Volume: Page:648-654
ISSN:
Container-title:2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS)
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Author:

Konidena Anuradha¹,Shanbhog Manjula²,Singh Swati³,Sharma Vikrant⁴,Jain Anuj Kumar⁵,Sharma Neha⁵

Affiliation:

1. IILM University,Department of CSE,Greater Noida,Uttar Pradesh

2. Christ University,Department of Computer Science,Ghaziabad,Uttar Pradesh,India

3. School of Computing MIT-ADTU,Department of Information Technology,Pune,India

4. Graphic Era Hill University,Dehradun,Uttarakhand,India

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

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10389811/10389819/10389846.pdf?arnumber=10389846

Reference18 articles.

1. Wheat rust disease detection techniques: a technical perspective

2. An Automated Approach for Accurate Detection and Classification of Kiwi Powdery Mildew Disease

3. Detecting Severity Levels of Cucumber Leaf Spot Disease using ResNext Deep Learning Model: A Digital Image Analysis Approach

4. Early Detection and Classification of Tomato Leaf Disease Using High-Performance Deep Neural Network

5. Hatred and trolling detection transliteration framework using hierarchical LSTM in code-mixed social media text

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