Research on Baggage Tray Recognition in Airports Based on Residual Neural Network

In recent years, civil aviation industry of China has made extraordinary achievements, and since the reform and ope ning up, civil aviation industry of China has entered a new era of rapid development, and the airport construction has also been de veloped continuously. At present, the wisdom civil aviation progr am proposed by the state is being implemented gradually. Wisdo m civil aviation refers to the application of new generation techno logies such as artificial intelligence, Internet of Things, cloud com puting, etc. to the civil aviation industry, making travel and logist ics to digital transformation, but there is still a lack of further dev elopment. Due to the diversified, non-standardized and non-speci fied characteristics of checked baggage, trays are introduced as t he carrier of checked baggage and baggage handling system in ai rports, but there are problems such as difficulties in tray recover y and low efficiency. To address this problem, this paper propose s the use of ResNet network architecture to identify whether a pal let is used or not and facilitate the systematic handling of pallet re covery work. The algorithm model proposed in this paper can ac hieve 95.17% accuracy in the problem of intelligent recognition $\mathbf{0}$ f whether a pallet is used or not, which verifies the effectiveness $\mathbf{0}$ f the network model for this problem and provides a favorable help for the development of smart civil aviation.