Multi-Layered classification of Plant diseases using AI approach

Medida Jayapal; Madduru Sambasivudu; Chiriki Usha; Mantri Gayatri; Potu Sai Manisha

doi:10.2991/978-94-6463-471-6_105

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Multi-Layered classification of Plant diseases using AI approach

Authors

Medida Jayapal¹, Madduru Sambasivudu², Chiriki Usha³^{, *}, Mantri Gayatri⁴, Potu Sai Manisha⁵

¹Assistant Professor,CSEGITAM University, Hyderabad, A.P, India

²Associate Professor, CSE, MRCET, Hyderabad, A.P, India

³Assistant professor, Department of CSEDIET, Visakhapatnam, A.P, India

⁴Associate Professor, CSE, MRCET, Hyderabad, A.P, India

⁵M.Tech Student, CSE, MRCET, Hyderabad, A.P, India

^*Corresponding author. Email: chusha@diet.edu.in

Corresponding Author

Chiriki Usha

Available Online 30 July 2024.

DOI: 10.2991/978-94-6463-471-6_105 How to use a DOI?
Keywords: — Crop disease detection; Crop disease classification; preprocessing; convolution neural network; Deep learning
Abstract: The growth rate of an agricultural sector is related to its capacity for innovation, and vice versa. Our Analysis is focused to employ various deep learning models to create an efficient Plant Disease Detection and Classification Networks (PDDC-Net).Preprocessing is the process of standardizing dataset images by removing various forms of noise.Additionally, the PDDC-Net utilizes a ResidualNetwork-based Convolution Neural Network for efficient feature extraction and classification, ensuring accurate operation. Suggested PDDC-Net model achieved satisfactory accuracy in detecting and classifying plant leaf diseases, as evidenced by test results.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
Series: Advances in Computer Science Research
Publication Date: 30 July 2024
ISBN: 10.2991/978-94-6463-471-6_105
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-471-6_105 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Medida Jayapal
AU  - Madduru Sambasivudu
AU  - Chiriki Usha
AU  - Mantri Gayatri
AU  - Potu Sai Manisha
PY  - 2024
DA  - 2024/07/30
TI  - Multi-Layered classification of Plant diseases using AI approach
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 1107
EP  - 1115
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_105
DO  - 10.2991/978-94-6463-471-6_105
ID  - Jayapal2024
ER  -

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