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Abstract：
This study aims to combine deep learning technology and user perception to propose an efficient design method that can meet the perceptual needs of users and enhance the competitiveness of products in the market. Firstly, the application development of sensory engineering and the research on sensory engineering product design by related technologies are discussed, and the background is provided. Secondly, the Kansei Engineering theory and the algorithmic process of the convolutional neural network (CNN) model are discussed, and theoretical and technical support is provided. A perceptual evaluation system is established for product design based on the CNN model. Finally, taking a picture of the electronic scale as an example, the testing effect of the CNN model in the system is analyzed. The relationship between product design modeling and sensory engineering is explored. The results show that the CNN model improves the \"logical depth\" of perceptual information of product design and gradually increases the abstraction degree of image information representation. There is a correlation between the user perception impression of electronic weighing scales of different shapes and the design effect of product design shapes. In conclusion, the CNN model and perceptual engineering have in-depth application significance in the image recognition of product design and the perceptual combination of product design modeling. Combined with the CNN model of perceptual engineering, product design is studied. From the perspective of product modeling design, perceptual engineering has been deeply explored and analyzed. In addition, the product perception based on the CNN model can accurately analyze the correlation between product design elements and perceptual engineering and reflect the rationality of the conclusion.
摘要：
本研究旨在将深度学习技术与用户感知相结合，提出一种能够满足用户感知需求并增强产品在市场上竞争力的高效设计方法。首先,讨论了感官工程的应用发展和相关技术在感官工程产品设计中的研究，并提供了背景。其次,讨论了感性工程理论和卷积神经网络(CNN)模型的算法过程，理论和技术支持。建立了基于CNN模型的产品设计感知评价体系。最后,以电子秤的照片为例，分析了CNN模型在系统中的测试效果。探讨了产品设计建模与感官工程的关系。结果表明，CNN模型提高了产品设计感知信息的“逻辑深度”，并逐渐增加了图像信息表示的抽象程度。不同形状的电子称重秤的用户感知印象与产品设计形状的设计效果之间存在相关性。总之,CNN模型和感知工程在产品设计的图像识别和产品设计建模的感知组合中具有深入的应用意义。结合感知工程的CNN模型,对产品设计进行了研究。从产品造型设计的角度,对感性工程进行了深入的探索和分析。此外,基于CNN模型的产品感知能够准确分析产品设计要素与感知工程之间的相关性,体现结论的合理性。
