Rice diseases detection and classification using attention based neural network and bayesian optimization

作者：

Highlights：

• Proposed an attention based neural network model for rice disease diagnosis.

• Combined Bayesian optimization for hyperparameters tuning.

• Achieved rice disease classification accuracy of 94.65%.

• Outperformed the performance of existing models in the literature.

• Analyzed the explainability of the proposed model.

摘要

•Proposed an attention based neural network model for rice disease diagnosis.•Combined Bayesian optimization for hyperparameters tuning.•Achieved rice disease classification accuracy of 94.65%.•Outperformed the performance of existing models in the literature.•Analyzed the explainability of the proposed model.

论文关键词：Deep learning,Rice diseases detection,Plant disease,Agriculture image analysis

论文评审过程：Received 24 September 2020, Revised 19 February 2021, Accepted 19 February 2021, Available online 18 March 2021, Version of Record 24 April 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114770