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Published (Version of Record)CC BY V4.0, Open Access
Journal article
Deep network with score level fusion and inference-based transfer learning to recognize leaf blight and fruit rot diseases of eggplant
Agriculture, Vol.12(8), Article 1160
2022
Abstract
Eggplant is a popular vegetable crop. Eggplant yields can be affected by various diseases. Automatic detection and recognition of diseases is an important step toward improving crop yields. In this paper, we used a two-stream deep fusion architecture, employing CNN-SVM and CNN-Softmax pipelines, along with an inference model to infer the disease classes. A dataset of 2284 images was sourced from primary (using a consumer RGB camera) and secondary sources (the internet). The dataset contained images of nine eggplant diseases. Experimental results show that the proposed method achieved better accuracy and lower false-positive results compared to other deep learning methods (such as VGG16, Inception V3, VGG 19, MobileNet, NasNetMobile, and ResNet50).
Details
- Title
- Deep network with score level fusion and inference-based transfer learning to recognize leaf blight and fruit rot diseases of eggplant
- Authors/Creators
- Md.R. Haque (Author/Creator)F. Sohel (Author/Creator)
- Publication Details
- Agriculture, Vol.12(8), Article 1160
- Publisher
- MDPI
- Identifiers
- 991005543085307891
- Copyright
- © 2022 by the authors
- Murdoch Affiliation
- Centre for Crop and Food Innovation; School of Information Technology; Food Futures Institute
- Language
- English
- Resource Type
- Journal article
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- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.17 Computer Vision & Graphics
- 4.17.128 Deep Visual Recognition
- Web Of Science research areas
- Agronomy
- ESI research areas
- Agricultural Sciences