A decision support system using hybrid AI based on multi-image quality model and its application in color design

Li, Mengshan; Lian, Suyun; Wang, Fan; Zhou, Yanying; Chen, Bingsheng; Guan, Lixin; Yan, Wu

doi:10.1016/j.future.2020.06.034

Cited by 9 publications

(2 citation statements)

References 32 publications

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“…22 Pouli et al presented a histogram reshaping technique for determining the degree of color match between original and target images. 23 To build optimal color design models and obtain excellent color schemes that meet user needs, researchers have proposed many color design methods using intelligent algorithms, such as gray theory, 24 support vector machines (SVMs), 25,26 fuzzy theory, 27 artificial neural networks (ANNs), [28][29][30] the KE system and rough sets. 1,31 Moreover, semantic difference and other methods have been successfully used to evaluate the relationship between product color and user emotion, providing ideas and methods for product color emotional design.…”

Section: Intelligent Color Matching Design Algorithmsmentioning

confidence: 99%

Emocolor: An assistant design method for emotional color matching based on semantics and images

Zhang

Wang

et al. 2023

Color Research & Application

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Much research has been done on the relationship between emotions and colors, and many color scheme recommendation tools have been developed. These tools can often help recommend a suitable color scheme to express a certain emotion, but it is still difficult to design satisfying schemes based on such recommendations. In this study, based on the Color Scheme Bible, Compact Edition, we developed Emocolor, which allows professionals to generate a large number of color schemes based on emotional words or emotional images. It is also used to iteratively optimize the generated color schemes based on an interactive genetic algorithm to find the color scheme design that best matches the user's emotion. Through the evaluation of tram color schemes based on emotional words, Emocolor can effectively generate tram color schemes that match users' emotions. It can also effectively transfer the emotion of an image with a single dominant color to a tram color scheme. In short, Emocolor can help professionals describe the relationship between emotion and color in a more accurate way and design emotional color schemes. Emocolor can be applied in advertising design, product design, interior design, and other fields.

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Section: Intelligent Color Matching Design Algorithmsmentioning

confidence: 99%

Emocolor: An assistant design method for emotional color matching based on semantics and images

Zhang

Wang

et al. 2023

Color Research & Application

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“…Due to the tailored learning opportunities, they offer, these technologies have a significant impact on education. AIbased DSS assesses each student's unique data to personalize resources and recommendations, increasing engagement and performance (Li et al, 2020). Additionally, data-driven decision-making tools help instructors track student achievement, improve educational methods, and simplify administrative responsibilities.…”

Section: Introductionmentioning

confidence: 99%

AI and big data-driven decision support for fostering student innovation in music education at private underground colleges

Liu

2023

J INFORM SYSTEMS ENG

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This study investigates the transformative impact of AI-based Decision Support Systems (DSS) and Big Data Analytics (BDA) on student innovation and employability skills in an era of rapid technological advancement, with a focus on the mediating role of technological acceptance and the moderating role of resource availability. This study, which draws on a wide range of educational contexts and data sources, gives complete knowledge of the complex links between technology adoption, student results, and contextual factors. The results of this study show how AI-based DSS and BDA have a significant impact on musical education. These technological advancements enable tailored instruction and foster students' creative thinking. In order to prepare students for a work market that is rapidly changing, they act as a catalyst for improving employability skills. The study, however, emphasizes the complicated dynamics at work. Technological Acceptance emerges as a major mediating component, underlining the significance of students and instructors freely and effectively accepting technological tools. Furthermore, as a moderating factor, Resource Availability takes center stage, emphasizing the need for equitable access to educational resources to ensure that technology-driven advantages are accessible to all. The results of this study have broad repercussions. The adoption of AI and BDA by educational institutions is encouraged as transformative technologies for enhancing the learning process. Policymakers must create regulations that support equal access to technology and promote an innovative culture in the classroom. This study highlights for students how important it is to adopt new technologies, realizing how important they are in determining both their academic and career paths.

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On Explanations for Hybrid Artificial Intelligence

Nolle,

Stahl,

El-Mihoub

2023

Lecture Notes in Computer Science

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A decision support system using hybrid AI based on multi-image quality model and its application in color design

Cited by 9 publications

References 32 publications

Emocolor: An assistant design method for emotional color matching based on semantics and images

Emocolor: An assistant design method for emotional color matching based on semantics and images

AI and big data-driven decision support for fostering student innovation in music education at private underground colleges

On Explanations for Hybrid Artificial Intelligence

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