Application of Deep Convolutional Neural Network Technology in Product Design Course

  • Tiejun Zhu, Qings ong Sang,Radouan Ait Mouha


The effective application of convolutional neural network in computer vision, natural language processing and other aspects, as well as the research and design of smart home system and the development and application of smart home product terminals, are the important direction of current product design industry. However, due to the influence of traditional concepts and models, the real-time follow-up and close combination of the above-mentioned knowledge content has not been effectively implemented in the current product design course in China's universities, resulting in a partial disjunction with the requirements of talents required by the society. Based on this situation and trend, this paper takes the innovative design of smart home wardrobe system as an example, through the application of artificial intelligence deep convolutional neural network and other technologies to carry out the case analysis and design of system function module, logic level and system interface, so as to bring specific design practice close to the development front of product design, and at the same time, adopt course follow-up survey, learner self-evaluation, achievements statistics and comparative analysis and other methods summarize the course effect, which not only promotes the learners' cognition and understanding of the frontier of product design technology, but also effectively stimulates their interest, significantly improves the course quality, course effect and learners' innovative practice ability of product design major, and provides experience for reference.

How to Cite
Tiejun Zhu, Qings ong Sang,Radouan Ait Mouha. (1). Application of Deep Convolutional Neural Network Technology in Product Design Course. Forest Chemicals Review, 541-561. Retrieved from