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Realizing the identification and settlement of fruits and vegetables that lack barcodes is a major problem in supermarket self-service settlement. In order to realize the identification and classification of fruits and vegetables in supermarkets on the settlement terminal equipment with limited resources, a fruit and vegetable identification algorithm based on neural network is proposed. Improve Alex Net by increasing the network width to improve recognition performance. Combined with hardware devices such as pressure sensors and cameras, experiments were conducted on the Raspberry Pi to complete the construction of a fruit and vegetable self-service settlement system. After experimental tests, the average recognition accuracy of the system for fruits and vegetables can reach 98.25%, and the total time for a single settlement is about 7.48 seconds, which is only 1/4 of the time for manual settlement, which meets the actual application requirements of the fruit and vegetable self-service settlement system.