SunNet: A Deep Learning Approach to Detect Sunflower Disease-Reference-Cited by-同舟云学术

SunNet: A Deep Learning Approach to Detect Sunflower Disease

Published:2023-04-11 Issue: Volume: Page:
ISSN:
Container-title:2023 7th International Conference on Trends in Electronics and Informatics (ICOEI)
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Author:

Sathi Taslima Akter¹,Hasan Md Abid¹,Alam Mohammad Jahangir¹

Affiliation:

1. Daffodil International University,Dept.of CSE,Dhaka,Bangladesh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10125569/10125286/10125676.pdf?arnumber=10125676

Reference28 articles.

1. Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification

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

3. Grapes leaf disease detection using convolutional neural network;ghosh;International Journal of Modern Agri-culture,2020

4. Deep Learning for Tomato Diseases: Classification and Symptoms Visualization

5. Automation of leaf disease prediction framework based on machine learning and deep learning in different crop species;zabeeulla;Algebraic Statistics,2022

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1. Decoding Sunflower Downy Mildew: Leveraging Hybrid Deep Learning for Scale Severity Analysis;2024 5th International Conference for Emerging Technology (INCET);2024-05-24

2. Enhancing Sunflower Disease Identification with CNN-SVM Integration;2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON);2023-12-29

3. Sunflower Disease Identification using Deep Learning: A data-driven approach;2023 26th International Conference on Computer and Information Technology (ICCIT);2023-12-13

4. TeenyNet: a novel lightweight attention model for sunflower disease detection;Measurement Science and Technology;2023-12-08

5. Harnessing the Power of Transfer Learning in Sunflower Disease Detection: A Comparative Study;Agriculture;2023-07-26