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MobileNetV2-Incep-M: a hybrid lightweight model for the classification of rice plant diseases

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Abstract

The complex structure of the automatic rice detection model results in a delay in identifying diseases and may require higher computational power. To overcome this challenge, we introduced a novel lightweight model called MobileNetV2-Incep-M. MobileNetV2-Incep-M, is designed for rice plant disease classification, aiming to balance efficiency and performance. It combines MobileNetV2 with a single Inception module to create a lightweight architecture. Leveraging transfer learning, the model initializes with pre-trained weights from MobileNetV2 on ImageNet. The Inception module is seamlessly integrated, followed by a max pooling layer for down sampling and parameter reduction. Lastly, a flatten layer and fully connected layer are added for classification purposes. During the training phase we utilized the k-fold cross validation method to reduce the training biasness. The proposed model attained a maximum testing accuracy of 98.75%, a testing loss of 0.0302, and is characterized by the minimal training parameters of 2,502,468, with an average training duration of 464.85 s. We evaluated the proposed model by comparing with five other models, namely InceptionV3, VGG19, MobileNet, MobileNetV2, and DenseNet201. The dataset consists of 5624 images, including Bacterial blight, Leaf Blast, and Brown Spot, and Healthy. The proposed model outperforms the other models, achieving higher accuracy and improved detection of rice plant diseases. Such lightweight model can contribute to the early identification and effective management of rice plant diseases, which can have a substantial impact on agricultural productivity and food security worldwide.

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Data availability

Dataset publicly available in a repository:

Mendeley Data and are available at the following URL: https://data.mendeley.com/datasets/fwcj7stb8r/1

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  1. Department of Computer Engineering, G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India

    Akash Arya & Pankaj Kumar Mishra

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  1. Akash Arya
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Arya, A., Mishra, P.K. MobileNetV2-Incep-M: a hybrid lightweight model for the classification of rice plant diseases. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-18723-w

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