Multilayer Convolution Neural Network for the Classification of Mango Leaves Infected by Anthracnose Disease
Shri Mata Vaishno Devi University · Maulana Azad National Institute of Technology
Abstract
Fungal diseases not only influence the economic importance of the plants and its products but also abate their ecological prominence. Mango tree, specifically the fruits and the leaves are highly affected by the fungal disease named as Anthracnose. The main aim of this paper is to develop an appropriate and effective method for diagnosis of the disease and its symptoms, therefore espousing a suitable system for an early and cost-effective solution of this problem. Over the last few years, due to their higher performance capability in terms of computation and accuracy, computer vision, and deep learning methodologies have gained popularity in assorted fungal diseases classification. Therefore, for this paper, a…
Citation impact
- FWCI
- 51.86
- Percentile
- 100%
- References
- 35
Authors
4- UPUday Pratap SinghCorresponding
Shri Mata Vaishno Devi University
- SSSiddharth Singh Chouhan
Shri Mata Vaishno Devi University
- SJSukirty Jain
Shri Mata Vaishno Devi University, Maulana Azad National Institute of Technology
- SJSanjeev Jain
Shri Mata Vaishno Devi University, Maulana Azad National Institute of Technology
Topics & keywords
- Convolutional neural network
- Convolution (computer science)
- Deep learning
- Computer science
- Artificial intelligence
- Artificial neural network
- Tree (set theory)
- Pattern recognition (psychology)