This paper aims to improve the accuracy and efficiency of image aesthetic classification in environmental art design and provide a more professional and convenient method. Based on the Mobile Edge Computing (MEC) and Convolution Neural Network (CNN) Deep Learning (DL) algorithm, the current situation and shortcomings of the existing image aesthetic classification are analyzed. Thereupon, the MEC technology is combined with CNN, and the MEC-based Image Recognition (IR) architecture and parallel Deep CNN-based aesthetic evaluation method are prop...
