Abstract
There are many related diseases in the process of crop planting, which reduces the quality and yield of crops. Faced with such a situation, the prevention of crop diseases has become a hot spot and has broad application prospects. This experiment uses the image recognition technology of machine vision to analyze and recognize crop diseases. Based on the features of machine vision that can capture details that cannot be observed by the human eye, with high accuracy and high efficiency, it provides accurate image recognition of crop diseases. In accordance with. In the process of selecting the SVM classifier for image classification, the kernel function and gamma parameters in the classifier were adjusted, and the kernel function and high accuracy parameter interval suitable for crop disease analysis were found.
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Zhou, Y., Zhang, K., Shi, Y., Cui, P. (2022). A Crop Disease Recognition Algorithm Based on Machine Learning. In: Jiang, D., Song, H. (eds) Simulation Tools and Techniques. SIMUtools 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-030-97124-3_38
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DOI: https://doi.org/10.1007/978-3-030-97124-3_38
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