Areca nut detection method based on neural network algorithm

The invention provides an areca nut detection method based on a neural network algorithm, and the method comprises a training stage comprising obtaining a training image data set, marking the trainingimage data set to construct a training sample, inputting the training sample into a convolutional neural network, obtaining a connection weight and an offset value of the convolutional neural network, and obtaining a convolutional neural network training model; a detection stage, comprising: acquiring an actual areca nut image as input into the convolutional neural network training model to obtain an areca nut detection result. According to the invention, the VGG convolutional neural network is used as a classifier for areca nut defect detection. Since the network structure is shared by the convolutional neural network weight, the complexity of a network structure is reduced, the number of weights is reduced, so that the classification speed is high. In addition, samples with suspected defects are used for traini