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Leaf-CAP: A Capsule Network-Based Tea Leaf Disease Recognition and Detection

Publication Type : Book Chapter

Publisher : CRC Press

Url : https://www.taylorfrancis.com/chapters/edit/10.1201/9781003391302-7/leaf-cap-alkha-mohan-jayakrishnan

Campus : Coimbatore

School : School of Engineering

Department : Computer Science and Engineering

Abstract : The primary leaf diseases affecting tea leaves and harming the entire plant are the focus of this study. Algal leaf spot, anthracnose, bird's eye spot, brown blight, grey blight, red leaf spot, white spot, blister blight, and scab are the main diseases that damage tea plants. A model for identifying tea leaf diseases based on CNN that requires the least amount of computational complexity and resources while producing accurate results is proposed in. The investigated disease includes algal leaf spot, anthracnose, bird's eye spot, brown blight, grey blight, red leaf spot, white spot, blister blight, and scab. The benchmark "tea sickness dataset" is diverse and has eight categories: algal leaf spot, anthracnose, bird's eye spot, brown blight, grey blight, red leaf spot, white spot, and healthy. The primary capsules are connected to the class-defining output capsules via a dynamic routing algorithm.

Cite this Research Publication : Alkha Mohan and Jayakrishnan Anandakrishnan, “Leaf-CAP: A Capsule Network-Based Tea Leaf Disease Recognition and Detection,” in Predictive Analytics in Smart Agriculture, edited by S. Krishnan, A. J. Anand, N. Prasanth, S. Goundar, and C. Ananth, CRC Press, 2023.

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