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This paper investigates the migration learning AlexNet-based algorithm for the recognition of assembly building structures and the recognition based on an improved algorithm, and gives an analysis of the results. The structure of AlexNet convolutional neural network is introduced and the basic principles of migration learning are analysed. The optimal model for the ceiling damage recognition task was obtained through parameter adjustment, with a test accuracy of 96.6%. The maximum improvementdoi:10.1155/2022/2326903 fatcat:vkkwjuifn5adfbyovc6z26kihq