| dc.description.abstract | In recent years, the demand for image recognition related applications based on deep learning methods has continued to increase, and the burden on developers has also doubled. Therefore, this paper designs a low-code image recognition platform to achieve rapid development purposes, and the MLP-Mixer which is the newly launched neural network model in 2021 is used as the neural network architecture of the system. This research has developed a graphical human-machine interface that allows users to quickly train and test neural network models, and uses three different image datasets for experiments and analysis, with accuracy rates of 85%, 96.5%, and 89.6%, respectively. It has also been verified that the platform can realize image recognition applications on different datasets. The MLP-Mixer image recognition low-code development platform proposed in this paper can be automatically completed by selecting the folder and inputting relevant parameters in the entire process of training, testing the model and classification prediction. This low-code feature allows Non-expert general users can also easily use. | en_US |