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Image-based disease classification in grape leaves using convolutional capsule network
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Image-based disease classification in grape leaves using convolutional capsule network
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Journal Article
Image-based disease classification in grape leaves using convolutional capsule network
2023
Overview
Crop protection is the prime hindrance to food security. Plant diseases destroy the overall quality and quantity of agricultural products. Grape is an important fruit and a major source of vitamin C nutrients. The automatic decision-making system plays a paramount role in agricultural informatics. This paper aims to detect the diseases in grape leaves using convolutional capsule networks. The capsule network is a promising neural network in deep learning. This network uses a group of neurons as capsules and effectively represents spatial information of features. The novelty of the proposed work relies on the addition of convolutional layers before the primary caps layer, which indirectly decreases the number of capsules and speeds up the dynamic routing process. The proposed method has experimented with augmented and non-augmented datasets. It effectively detects the diseases of grape leaves with an accuracy of 99.12%. The method's performance is compared with state-of-the-art deep learning methods and produces reliable results.
Publisher
Springer Berlin Heidelberg
