Tobacco leaf mildew detection system based on artificial intelligence

Abstract

The invention discloses a tobacco leaf mildew detection system based on artificial intelligence, and relates to the technical field of tobacco production. The system comprises a semantic segmentationmodule, a mildewing position image forming module, a mildewing analysis module, a mildewing position acquisition module and a mildewing detection condition visualization module, and all nodes in a cloud server cluster are loaded into required parameters and weights detected by a mildewing detection system to generate a mildewing detection network reasoning block private chain; for each neural network reasoning request, available nodes are randomly selected from the cloud server cluster, a node chain sequence matched with the mildew detection network reasoning block private chain is obtained, mildew detection network reasoning is executed in parallel, and therefore tobacco mildew detection is achieved. According to the tobacco leaf mildew detection system based on artificial intelligence, traditional manual detection is not needed, tobacco leaf mildew detection is conducted through artificial intelligence, the detection efficiency and precision are improved, and the safety performance in the data processing process is improved.

Description

technical field [0001] The invention relates to the technical fields of artificial intelligence and blockchain, in particular to an artificial intelligence-based tobacco mildew detection system. Background technique [0002] my country is a big country in tobacco leaf production and consumption. In the production of cigarettes, the tobacco leaf raw materials must first be selected and classified. The quality of the selected tobacco leaves is directly related to the purity and quality of the produced cigarettes. Therefore, it is very important to select and classify tobacco leaf raw materials. Whether the tobacco leaves are moldy or not is a key indicator for classifying tobacco leaves. At present, there are researches on mildew detection based on image processing technology, but the detection accuracy and detection efficiency are often not high. Moreover, in the mildew detection process, factors such as security are not considered, and the processed data is easily attack...

AI Technical Summary

Problems solved by technology

At present, there are researches on mildew detection based on image processing technology, but the detection accuracy and detection efficiency are often not high

Moreover, in the process of mildew detection, factors such as security are not considered, and the processed data is easily attacked and intercepted

Therefore, the existing tobacco mildew detection technology has the problems of low detection accuracy and detection efficiency, and low security in the data processing process.

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