Inner Mongolia is rich in grassland tourism resources, and the development of grassland tourism is of great significance to Inner Mongolia tourism and promotion of grassland protection. To better promote the grassland tourism of the Silk Road culture, the Conditional Global Area Network (CGAN) and Morphology Connected Component Chan-Vase (MCC-CV) algorithm are used to enhance and segment the traditional embroidery patterns in Inner Mongolia. Firstly, the generative adversarial network (GAN) is optimized, and a new GAN is proposed with the feature vector extracted from the convolutional neural network (CNN) as the constraint condition. Secondly, the automatic segmentation algorithm of embroidery based on the MCC-CV model is proposed, and finally, the proposed algorithm is tested. The test results demonstrate that after 8000 iterations of the proposed image-enhancement algorithm, its personalized features are enhanced, and the segmentation accuracy of the proposed image segmentation algorithm is 60%. The proposed algorithm provides some ideas for the application of deep learning (DL) technology in the grassland tourism of the Silk Road culture and also helps operators to accurately grasp the market and make tourists more comfortable and pleasant.
Art teaching is not only an important part of basic education but also an important subject of core literacy education, and the cultivation of core literacy is also a long and lasting process. In order to change the original teaching mode, reform the teaching concept, and cultivate high-quality all-round talents, this paper integrates artificial intelligence interactive teaching method into the art teaching process from the perspective of core literacy, which can not only increase the classroom interaction, improve students’ enthusiasm, and conduct multidimensional evaluation on students’ art work performance, moral sentiment, appreciation ability, creativity, and imagination. While paying attention to cultivating and improving students’ comprehensive quality and ability, the all-round development of students’ moral, intellectual, physical, artistic, and labor ability is improved.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.