Huaning Song1, Jiansheng Peng1,2,*, Nianyang Tuo1, Haiying Xia2, Yiyun Peng3
Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 581-592, 2021, DOI:10.32604/iasc.2021.014152
Abstract Accurate identification of sugarcane buds, as one of the key technologies in sugarcane plantation, becomes very necessary for its mechanized and intelligent advancements. In the traditional methods of sugarcane bud recognition, a significant amount of algorithms work goes into the location and recognition of sugarcane bud images. A Convolutional Neural Network (CNN) for classifying the bud conditions is proposed in this paper. Firstly, we convert the colorful sugarcane images into gray ones, unify the size of them, and make a TFRecord format data set, which contains 1100 positive samples and 1100 negative samples. Then, a CNN mode is developed to… More >
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