• Journal of Fashion Business
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• v.19 no.1
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• pp.122-140
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• 2015

The research is committed to inquire about the attributes of color schemes and their image, and the results are as follows : One, the preference of ranges of neon colors was explicit, and the frequency of use of neon colors distinctively diverged season by season. Two, it was observed that, with neon colors, an achromatic color scheme was a more preferred arrangement. As for chromatic colors, neutral and mid-tone natural colors were more favored since they did not tarnish the properties of neon colors and, yet, more effective exhibiting images in diversity and variety. Three, the neon color fashion generally displayed a dual image: its original classification embellished with neon colors rendering the image of powerful and futuristic sensation. Having been around since the early 2000's, the frequency and range of use of neon colors have been increasing rapidly mostly by the sports, leisure and related industries. Regardless of the fact, neon colors will be rediscovered with a variety of color schemes and expand their application.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.2
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• pp.354-368
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• 2020

Accurate and versatile image data-sets are essential for fashion AI research and AI-based fashion businesses based on a systematic attribute classification system. This study constructs a color and texture attribute hierarchical classification system by collecting fashion item images and analyzing the metadata of fashion items described by consumers. Essential dimensions to explain color and texture attributes were extracted; in addition, attribute values for each dimension were constructed based on metadata and previous studies. This hierarchical classification system satisfies consistency, exclusiveness, inclusiveness, and flexibility. The image tagging to confirm the usefulness of the proposed classification system indicated that the contents of attributes of the same image differ depending on the annotator that require a clear standard for distinguishing differences between the properties. This classification system will improve the reliability of the training data for machine learning, by providing standardized criteria for tasks such as tagging and annotating of fashion items.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.384-395
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• 2006

Topographical images such as aerial and satellite images are usually similar with respect to colors and textures but not in shapes. Thus shape features of the images and the methods of extracting them become critical for effective image retrieval from topographical image databases. In this paper, we propose a shape feature extraction method for topographical image retrieval. The method extracts a set of attributes which can model the presence of holes and disconnected regions in images and is tolerant to pre-processing, more specifically segmentation, errors. Various experiments suggest that retrieval using attributes extracted using the proposed method performs better than using existing shape feature extraction methods.

• The Korean Journal of Franchise Management
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• v.15 no.2
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• pp.39-56
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• 2024

Purpose: Delivery food continues to grow. In the past, restaurant companies directly hired delivery workers to deliver food, but now, restaurant companies use delivery service platform companies to carry out delivery work rather than directly hiring delivery workers. Therefore, this study seeks to determine the impact of delivery food benefits in the restaurant industry on brand image, trust, and word-of-mouth intention. Research design, data, and methodology: To test the hypotheses of this study, 400 questionnaires were distributed and 340 were collected. Among these, 321 questionnaires, excluding 19 questionnaires that were answered insincerely, were used in the final analysis. Result. First, delivery food benefits were found to have a significant impact on brand image and trust. Second, brand image was found to have a significant effect on trust and word-of-mouth intention. Third, trust was found to have a significant effect on word-of-mouth intention. Conclusions: First, existing research focused on studying the attributes of delivery food in the restaurant industry, but this study studied the benefits that consumers can obtain through purchase among these attributes. Second, delivery food restaurants need to design promotions and advertisements in a way that displays coupons, points, or mileage. Third, quick delivery of orders can be a competitive advantage for delivery food restaurants.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.251-258
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• 2010

'Naturalness' is the important "ness" which is a key factor in image quality assessment. 'Naturalness' is a representive factor depending on the context of the image which arouses different emotions. The Image Quality Circle was split into two steps. The first step is predicting the visual perceptual attribute which are lightness, colourfulness, hue and contrast. The next step is SSE which is dependent to image contents. In this study the image contents are grouped in genres. The images were rendered using four different colour attributes which are lightness, contrast, colourfulness and hue. Using a scale, the score of image quality and SSE was asked to each participant for all rendered images. A seven-point category scale of increasing amount of "ness" is used as a quantitative adjectives sequence. The image quality model was built by combining the SSEs for each scene. The SSEs, where vividness is common, are considered as independent variables to predict the image quality score. Then the vividness model was built using colour attributes as variables to predict the vividness of each scene (genre). Vividness is an important factor of naturalness which the meaning is different for all scenes that links the naturalness and image quality. The vividness meaning was different for each scene (genre). Therefore, the colour attributes that express the vividness would depend on the image content.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.27-37
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• 2016

This study examined consumer perceptions towards outdoor wear differentiation and product attributes for outdoor wear differentiation to develop an outdoor wear differentiation strategy. It also investigated how consumer's evaluated product attributes according to consumer's demographic characteristics. Data were acquired from a survey of 454 adult respondents aged over 20 that was analyzed with descriptives, frequency, t-test, one-way ANOVA, factor analysis, and reliability. The results were as follows. First, it showed that consumers did not have a positive or a negative perception toward outdoor wear differentiation, and they thought outdoor wear should be differentiated. Those married and older tended to think that outdoor wear should be differentiated more than that for those single and younger. Consumer evaluations were significantly different on the necessity of outdoor wear differentiation according to age and total income. Second, consumers assessed that color, pattern and textiles had similar characteristics among outdoor wear brands; in addition, brand recognition and brand image had very different characteristics. Third, product attributes for outdoor wear differentiation were service and store, product quality, brand and popularity, and product designs with mean values of product quality, product design, service and store, and brand and popularity, respectively. Fourth, consumers were significantly different in the importance assessment of product attributes for differentiation according to gender, marital status and age.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.589-603
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• 2023

Deep generative models target to infer the underlying true data distribution, and it leads to a huge success in generating fake-but-realistic data. Regarding such a perspective, the data attributes can be a crucial factor in the data generation process since non-existent counterfactual samples can be generated by altering certain factors. For example, we can generate new portrait images by flipping the gender attribute or altering the hair color attributes. This paper proposes counterfactual disentangled variational autoencoder generative adversarial networks (CDVAE-GAN), specialized for data attribute level counterfactual data generation. The structure of the proposed CDVAE-GAN consists of variational autoencoders and generative adversarial networks. Specifically, we adopt a Gaussian variational autoencoder to extract low-dimensional disentangled data features and auxiliary Bernoulli latent variables to model the data attributes separately. Also, we utilize a generative adversarial network to generate data with high fidelity. By enjoying the benefits of the variational autoencoder with the additional Bernoulli latent variables and the generative adversarial network, the proposed CDVAE-GAN can control the data attributes, and it enables producing counterfactual data. Our experimental result on the CelebA dataset qualitatively shows that the generated samples from CDVAE-GAN are realistic. Also, the quantitative results support that the proposed model can produce data that can deceive other machine learning classifiers with the altered data attributes.

• Journal of Korean Society of Rural Planning
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• v.12 no.2 s.31
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• pp.1-9
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• 2006

Current environmental problems of rural area are connected to loss of rural functions which is food security as well as conservation of environment, balanced development of country and succession of traditional culture. To solve these problems, recent projects are focusing on social changes in rural area and conservation of rurality creating values of rural amenity resources. At this point, full implications of rurality which is the various aspects of rurality should be defined to be applied in direct plans to conserve the rurality. In this study, nine attributes of rurality are found as various meanings with adjectives included in image of rurality. For practical use of these adjectives of rurality attributes, we evaluate the list of rural amenity resources and suggested plans for conservation of rural amenity. These attributes can be used as an effective method for village plan which brings one of the attributes into relief.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.10
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• pp.1509-1521
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• 2008

The subjects of this study were middle-aged women in their 40s$\sim$50s and older women aged 60 and over who were living in Seoul and Kyonggi-do, Korea. Through studying the participants' responses to the questions regarding the attributes of apparel quality in terms of the levels of satisfaction and importance, the target consumers' demand has been studied. And, they are applied to a QFD Matrix, to find out the relationship between the attributes of product quality and the guidelines of clothing design. For this study, apparel product quality is composed of five parameters: practicality, aesthetics, brand image, ease of care and fit. For the parameters of apparel product quality, the result of this study show that product improvements are needed in fit, aesthetics and practicality(in order of importance). The level of satisfaction(how satisfied consumer feels) was marked higher in brand image than that of importance(how important it is). To review demands for the apparel product attributes of formal suits for middle-aged and older women, the priority of these attributes through QFD Matrix that shows the relationship between the attributes and dress elements emphasized by designers has been examined. Material was the most important design element in designing formal suits. The shape of the pants was the second because the harmony between the jacket and the pants is important in formal suits. These were followed by trim and color tone of the jacket.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.137-146
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• 2017

This study explores the impacts of application attributes of coffee chains on consumer's re-purchase decision-making processes in the context of coffee chains. We posited coffee quality, service quality, and physical environment as key service attributes of coffee chains and personalization, usefulness, economy, and convenience as key application attributes. The moderating effect of application attributes on the relationship between consumer satisfaction and repurchase intention was investigated. The theoretical framework was tested based on 382 consumers who frequently visit coffee chains and install their applications. PLS method was used to analysis the hypotheses. The theoretical model accounts for 48.1% of variance in customer satisfaction and 41.6% of variance in repurchase intention. The analysis results showed that personalization and convenience play an moderating effect on consumer's repurchase decision-making processes. Coffee quality and physical environment were found to have significant effects on customer satisfaction, while service quality does not significantly influence consumer satisfaction. Brand image has a significant effect on customer satisfaction and repurchase intention.