Decoding Sunflower Downy Mildew: Leveraging Hybrid Deep Learning for Scale Severity Analysis-Reference-Cited by-同舟云学术

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Decoding Sunflower Downy Mildew: Leveraging Hybrid Deep Learning for Scale Severity Analysis

Published:2024-05-24 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 5th International Conference for Emerging Technology (INCET)
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Author:

Banerjee Deepak¹,Sharma Neha¹,Upadhyay Deepak²,Singh Mukesh³,Chythanya Kanegonda Ravi⁴

Affiliation:

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

2. Computer Science & Engineering Graphic Era Hill University,Dehradun,Uttarakhand,India,248002

3. Graphic Era Deemed to be University,Dehradun,Uttarakhand,India

4. School of Computer Science & Artificial Intelligence, SR University,Warangal

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592862/10592849/10592879.pdf?arnumber=10592879

Reference14 articles.

1. Classification of Sunflower Foliar Diseases Using Convolutional Neural Network

2. Automatic Segmentation and Classification System for Foliar Diseases in Sunflower

3. Mapping Infected Crops Through UAV Inspection: The Sunflower Downy Mildew Parasite Case

4. ResNet interpretation methods applied to the classification of foliar diseases in sunflower

5. TeenyNet: a novel lightweight attention model for sunflower disease detection

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