Multi-Scale Features Fusion Convolutional Neural Networks for Rice Leaf Disease Identification

Ching-Ling Wang; Mu-Wei Li; Yung-Kuan ChanShyr-Shen YuJie Hao OuChi-Yu ChenMiin-Huey LeeChuen-Horng Lin

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Multi-Scale Features Fusion Convolutional Neural Networks for Rice Leaf Disease Identification

机译：Multi-Scale Features Fusion Convolutional Neural Networks for Rice Leaf Disease Identification

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It is time-consuming and labor-intensive to detect rice diseases manually. The purpose of this research is to develop a convolutional neural networks (CNNs)-based system to automatically detect the diseased rice leaf infected with rice leaf blast, helminthosporium leaf blight, and bacterial leaf blight. The sizes of rice leaf spots vary with the severity of disease infection. A single model based CNN cannot effectively classify images, especially for images with objects of small size as well as multiple object scales, and complicated image background. In this research, a multiscale serial convolution neural network (MSSCNN) and a multiscale parallel convolution neural network (MSPCNN) are proposed to identify diseased rice leaf spots based on multi-modal fusion to extract different perception features and combine them to improve the performances obtained by using only one modality. Experimental results delineate that MSSCNN and MSPCNN can get better performance in identifying the diseased rice leaves. In MSPCNN, the features of tiny spots on diseased rice leaves can be completely preserved. MSPCNN can hence offer better performances than MSSCNN. Additionally, MSPCNN architecture is suitable for parallel computing environment.

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《Journal of Imaging Science and Technology》 |2022年第5期|50501.1-50501.12|共12页
作者
Ching-Ling Wang; Mu-Wei Li; Yung-Kuan ChanShyr-Shen YuJie Hao OuChi-Yu ChenMiin-Huey LeeChuen-Horng Lin;
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Department of Information Management, National Chin-Yi University of Technology;

Department of Computer Science and Engineering, National Chung Hsing University;

Department of Management Information Systems, National Chung Hsing UniversityDepartment of Plant Pathology, National Chung Hsing UniversityDepartment of Computer Science and Information Engineering, National Taichung University of Science and Technology;

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Multi-Scale Features Fusion Convolutional Neural Networks for Rice Leaf Disease Identification

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