The identification of 5G communication target signal type may be the premise and foundation of modulation mode identification, signal demodulation and other links. Therefore, the identification of 5G communication target signal type has become an indispensable technical link in the intelligent signal processing system. In order to solve the shortcomings of existing agricultural machine vision system research, this paper discusses the composition and key technologies of agricultural machine vision system and machine learning algorithm, and then simply discusses the hardware selection and software development environment of the system in which the algorithm proposed in this paper is applied. And the overall results of agricultural machine vision monitoring system are designed and discussed. RCNN and K-means algorithms in machine learning are used to study the identification and classification of seedlings in images. Finally, through the experimental analysis of selected samples, it is known that the accuracy of RCNN and K-means algorithm in image recognition detection in agricultural machine vision monitoring system is up to 94.25%. Therefore, it is verified that machine learning algorithm has high practical value in agricultural machine vision system.

Yuxin Ding. Target Signal Recognition Method for 5G Communication Supporting Machine Learning. Machine Learning Theory and Practice (2022), Vol. 3, Issue 2: 57-65. https://doi.org/10.38007/ML.2022.030207.

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