Research on the construction method of kansei image prediction model based on cognition of EEG and ET

Yang, Mo; Chen, Zhiang; Wu, Lei; Guo, Zhuen

doi:10.1007/s12008-020-00651-2

Cited by 15 publications

(6 citation statements)

References 41 publications

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“…Wang et al used the semantic difference method to measure users' image needs, obtained key image words through factor analysis, and used partial correlation analysis to determine the connection between design elements and images [10]. Yang et al introduced electroencephalogram (EEG) and eye tracking (ET) technologies to establish a space for user image needs and used partial least-squares regression to establish a correlation model between shape design elements, EEG and ET indicators, and image values [11].…”

Section: A Image Evaluation Of Product Formsmentioning

confidence: 99%

Optimization Design of Product Form Driven by Image Cognitive Friction

Ouyang,

Huang,

Zhang

et al. 2023

IEEE Access

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To balance the image cognitive friction of users and designers regarding product form, based on noncooperative game theory, a product form optimization design method was proposed to generate product forms that meet the common expectations of users and designers. First, the semantic difference method was used to construct the image cognitive spaces of users and designers. Second, based on the theory of computational aesthetics, production rules were used to structurally describe the aesthetic knowledge of product form; the aesthetic index values of product form were calculated; and two gray-box image evaluation models of design features, aesthetic indexes, and images were established with the method of quadratic polynomial stepwise regression. Finally, using the image cognitions of users and designers as game participants and the two image evaluation models as profit functions, a noncooperative game model was established, and a quantum genetic algorithm was used to obtain the Nash equilibrium solution of the model to achieve the optimal design of the product form. Taking the optimal design of a sphygmomanometer as an example, the rationality and effectiveness of the method are verified.

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Section: A Image Evaluation Of Product Formsmentioning

confidence: 99%

Optimization Design of Product Form Driven by Image Cognitive Friction

Ouyang,

Huang,

Zhang

et al. 2023

IEEE Access

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“…Digital government resource platform is a critical component of the education system; the construction and sharing of the platforms are considered the key to digital education. They are recognized by some scholars [ 15 ]. Lemon Tree School in California has centralized and established a unique online resource platform with corresponding digital teaching tools.…”

Section: Related Workmentioning

confidence: 99%

Research on the Multimodal Digital Teaching Quality Data Evaluation Model Based on Fuzzy BP Neural Network

Feng

2022

Computational Intelligence and Neuroscience

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We propose in this paper a fuzzy BP neural network model and DDAE-SVR deep neural network model to analyze multimodal digital teaching, establish a multimodal digital teaching quality data evaluation model based on a fuzzy BP neural network, and optimize the initial weights and thresholds of BP neural network by using adaptive variation genetic algorithm. Since the BP neural network is highly dependent on the initial weights and points, the improved genetic algorithm is used to optimize the initial weights and thresholds of the BP neural network, reduce the time for the BP neural network to find the importance and points that satisfy the training termination conditions, and improve the prediction accuracy and convergence speed of the neural network on the teaching quality evaluation results. The entropy value method, a data-based objectivity evaluation method, is introduced as the guidance mechanism of the BP neural network. The a priori guidance sample is obtained by the entropy method. Then, the adaptive variational genetic algorithm is used to optimize the BP neural network model to learn the a priori sample knowledge and establish the evaluation model, which reduces the subjectivity of the BP neural network learning sample. To better reflect and compare the effects of the two neural network evaluation models, BP and GA-BP, the sample data were continued to be input into the original GA and BSA to obtain the evaluation results and errors; then, the evaluation results of the two evaluation models, BP and GA-BP, were compared with the evaluation results of the two algorithms, GA and BSA. It was found that the GA-BP neural network evaluation model has higher accuracy and can be used for multimodal digital teaching quality evaluation, providing a more feasible solution.

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“…And the selection rate under the "heavy" image vocabulary is a � . When � > � , the image attribute of the sample is "light", the attribute of the sample is "heavy", to establish the formula (5). Based on the analysis of implicit measurement data, a high correlation model between each data and image value is established.…”

Section: Establishment Of Correlation Of Subject Selection Rate Datamentioning

confidence: 99%

“…But it also has many shortcomings: for the explicit behaviors displayed by users after their subjective consciousness, users are vulnerable to external interference, resulting in users reducing their true consciousness of expressing their hearts. If users want to express real consciousness, they will often be affected by the experience, knowledge level, etc., and their explicit behaviors cannot be controlled by real consciousness [5]. Therefore, the traditional explicit measurement method can only analyze the explicit behavior of users, cannot detect the real conscious cognitive process of users, and cannot reach a highreliability level [6].…”

Section: Introductionmentioning

confidence: 99%

Research on Image Acquisition Method Model Based on Implicit Association Test

Guo

2020

E3S Web Conf.

Self Cite

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In the process of the traditional quantitative method is easily interfered with by subjective and external environment, and cannot reflect the real emotion of users. The implicit measurement method can better reflect the cognitive of users and has good reliability in perceptual evaluation. In this paper, the implicit cognitive processing process in users’ perceptual evaluation of products is quantitatively analyzed. The correlation between product image attribute values and implicit measurement data is obtained. Thus, an image extraction model based on implicit measurement data is obtained. The implicit association test is introduced into the image extraction process, and the relationship between the implicit association test data of users and the data of product image attribute values is analyzed. Taking UAV as the analysis prototype, the image extraction model is obtained. After verification and analysis, the image extraction results are consistent with the image attribute values.

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Research on the construction method of kansei image prediction model based on cognition of EEG and ET

Cited by 15 publications

References 41 publications

Optimization Design of Product Form Driven by Image Cognitive Friction

Optimization Design of Product Form Driven by Image Cognitive Friction

Research on the Multimodal Digital Teaching Quality Data Evaluation Model Based on Fuzzy BP Neural Network

Research on Image Acquisition Method Model Based on Implicit Association Test

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