Identifying Brand Consistency by Product Differentiation Using CNN

作     者：Hung-Hsiang Wang Chih-Ping Chen 

作者机构：Department of Industrial DesignNational Taipei University of TechnologyTaipeiTaiwan Department of Product DesignMing Chuan UniversityTaoyuanTaiwan 

出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)

年 卷 期：2024年第140卷第7期

页      面：685-709页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by a grant PHA1110214 from MOE Taiwan 

主　　题：Machine learning product differentiation brand consistency principal component analysis convolutional neural network computer mouse 

摘      要：This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance *** Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and *** show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various *** investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late *** show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real *** relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style *** addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred *** study provides insights into practical problems for designers,manufacturers,and marketers in product *** not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand *** can use these techniques to find features that influence brand ***,capture these features as innovative design elements and maintain core brand values.