• Smart Media Journal
• /
• v.13 no.4
• /
• pp.57-64
• /
• 2024

Attributes such as material, color, and fit in fashion images are important factors for consumers to purchase clothing. However, the process of classifying clothing attributes requires a large amount of manpower and is inconsistent because it relies on the subjective judgment of human operators. To alleviate this problem, there is a need for research that utilizes artificial intelligence to classify clothing attributes in fashion images. Previous studies have mainly focused on classifying clothing attributes for either tops or bottoms, so there is a limitation that the attributes of both tops and bottoms cannot be identified simultaneously in the case of full-body fashion images. In this study, we propose a deep learning model that can distinguish between tops and bottoms in fashion images and classify the category of each item and the attributes of the clothing material. The deep learning models ResNet and EfficientNet were used in this study, and the dataset used for training was 1,002,718 fashion images and 125 labels including clothing categories and material properties. Based on the weighted F1-Score, ResNet is 0.800 and EfficientNet is 0.781, with ResNet showing better performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.10a
• /
• pp.57-58
• /
• 2013

스마트 기기의 급속한 보급으로 다양한 모바일 어플리케이션들이 개발되고 있으며 여러 성공 사례도 발표되고 있다. 본 논문에서는 다양한 어플리케이션 도메인 중 SNS와 결합한 패션 콘텐츠 앱의 설계를 제안한다. 제안하는 앱은 기존 온라인 쇼핑몰의 통일되지 않은 치수 정보를 보완하고 SNS와의 결합을 통해 패션정보 공유 및 교류를 가능하도록 한다.

• Journal of Fashion Business
• /
• v.17 no.4
• /
• pp.149-163
• /
• 2013

This study investigated the effects of smart phone usage motives and fashion brand app factors upon the intention to accept fashion brand applications. Data were collected from 250 female college students living in Seoul and Gyeonggi-do. 220 reliable data were analyzed by frequency, factor analysis, Cronbach's alpha, ANOVA,, Duncan test, paired t-test, chi-square analysis, regression. The results were as follows: Firstly, the 'information acquisition' and the'use of time' were considered to be the most important motive factors driving consumer's smart phone usage. Secondly, the motives underpinning smart phone user's intention to accept a fashion brand application were 'social relationships', 'entertainment', and 'information acquisition'. Thirdly, the frequently used factors during the usage of fashion brand application could be classified in order of frequency as follows: 'product information provision', 'store information provision', 'coordinated information provision', 'fashion information provision', 'entertainment provision', 'hobbies and life information provision', virtual wearing provision', 'SNS provision', and, 'events and coupons provision'. Fourthly, a factor analysis of these nine factors were classified into 'basic information type', and 'additional information type'. The influences of basic information type and the additional information type upon the intention to accept the fashion brand application showed the following significant result: The basic information type had a greater influence upon the intention to accept the fashion brand app.

• Fashion Information and Technology
• /
• v.11
• /
• pp.50-55
• /
• 2014

• Fashion & Textile Research Journal
• /
• v.18 no.6
• /
• pp.825-832
• /
• 2016

The purposes of this study was to investigate effects of fashion brand apps on smartphones flow and consumer satisfaction in mobile shopping. These findings provide new information to marketers for the marketing strategy for dealing with mobile shopping mall. A total of 233 usable questionnaires were obtained from men and women ages 20-30 who have mobile shopping purchasing experience. Data were analyzed by frequency analysis, factor analysis using SPSS for Window 22.0 and confirmatory factor analysis and structural equation model analysis by AMOS 22.0. The results were as follows. First, the analysis of fashion brand apps factors showed that it consist of 2 kinds of dimensions of basic information type and additional information type. Second, basic information type of fashion brand apps have had a direct impact on consumer satisfaction and did not affect the smartphones flow. Additional information type influence consumer satisfaction through a smartphones flow. Basic information type of fashion brand apps showed a greater impact on consumer satisfaction than a smartphone flow. A managerial implication was discussed for fashion brand marketers to develop strategies on fashion brand apps that could stimulate and increase the consumer flow and satisfaction.

• Fashion & Textile Research Journal
• /
• v.22 no.1
• /
• pp.55-65
• /
• 2020

Smart photonic clothing integrates light emitting technology inside and outside of the garment and integrates it as a fashion product. It expresses digital color that radiates light outside the body that expands the functionality of the clothing as well as makes new and various attempts visually. It is also is gradually expanding into a new area of fashion. LED, one of the digital color output devices, is a light emitting device that is suitable for presenting consumer customized designs in that the patterns and colors of clothes can be modified as desired by utilizing computer technology such as program coding. LED technology that can realize various digital colors is actively applied in various industrial design fields, but there are few previous studies on smart clothes using LED color in Korean fashion fields. Therefore, this study develops a prototype of a customized LED smart photonic garment that allows the user to directly participate in the color implementation of clothing and select a digital color suitable for the desired function. The LED module was designed to be detachable from clothing and made using a 256-pixel LED matrix. Various coding patterns of the LED were designed using the coding change of Arduino program.

• Proceedings of the Korea Contents Association Conference
• /
• 2010.05a
• /
• pp.342-344
• /
• 2010

스마트웨어가 사용자 중심으로 다변화 되어가는 유비쿼터스 환경속에서 상황정보를 제공하는 것은 서비스 전략의 중요한 성공요소가 되고 있다. 상황인식은 현실의 상황을 정보화하고 이를 활용하여 지능화된 개인화 서비스를 제공하는 기술이다. 본 논문에서는 상황인식을 이용한 맞춤형 패션 디자인 스타일 추천을 제안하였다. 제안된 방법은 사용자에게 자신의 선호도에 부합하는 패션 디자인 스타일을 제공함으로써 이를 얻기 위한 시간과 비용을 줄여주고, 손쉽게 원하는 스타일에 접근하도록 한다. 상황인식은 개인화 서비스에 필요한 상황정보를 추출하고 분류한다. 그리고 상황인식 기반의 필터링으로 패션 디자인 스타일 추천을 함으로 사용자에게 보다 다양한 서비스를 제공할 수 있다. 이를 사용자 인터페이스로 구축하여 논리적 타당성과 유효성을 검증하기 위해 실험적인 적용을 시도하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.11a
• /
• pp.922-924
• /
• 2022

본 연구에서는 2D 이미지 파일을 NFT 3D 패션 아이템으로 변환하여 거래할 수 있도록 한다. 한 장의 2D 이미지가 SMR을 통해 3D 오브젝트로 변환된다. 변환된 오브젝트는 KIP-17 기반의 스마트 컨트랙트를 통해 NFT을 발행할 수 있도록 환경을 구축하고, 최종적으로 NFT를 거래할 수 있는 플랫폼을 제공한다.

• Smart Media Journal
• /
• v.13 no.6
• /
• pp.80-89
• /
• 2024

This study aims not only to address environmental issues caused by indiscriminate fashion consumption, specifically in the context of Fast Fashion but also to find an alternative and a sustainable solution that is 'Upcycling' using the 3D clothing simulation program Z-weave. Upcycling products have limitations in that it is difficult to produce samples since finished products must be produced directly with limited materials and resources like waste clothes. To overcome these limitations, a 3D clothing simulation program is introduced to effectively utilize the limited resources of waste clothing. The purpose of this study is to confirm the similarity between a virtual fabric created through Z-weave and a real fabric, through this, to evaluate the possibility of application in the actual fashion industry. As a research method, surveys and interviews were conducted with related majors on virtual clothing created as similar as possible to actual clothing by adjusting the physical properties within the Z-weave program. This study attempted to describe the impact of digital technology on the fashion industry and how 3D clothing simulation programs can be used in sustainable fashion production.

• Fashion & Textile Research Journal
• /
• v.23 no.1
• /
• pp.84-97
• /
• 2021

This study examines the impact of perceived risks for smart shoes based on purchase intention by type of smart shoes as well as how they are mediated by fashion innovativeness and technology innovativeness. It also compares the differences between awareness, interest and perceived risk of smart shoes by gender and age. This study was conducted based on men and women in their 20s to 50s who provided 246 samples for data analysis using SPSS 25.0. The results show significant differences in the awareness, interests and perceived economic risk of smart shoes by gender and age. The perceived performance risk had a positive effect on the purchase intention of smart shoes for GPS. Perceived aesthetic-psychological risk had a negative effect on all types of smart shoes. Perceived economic risk had a negative effect on the purchase intention of smart shoes for entertainment; in comparison, perceived social risk had a positive effect on the purchase intention of smart shoes for GPS and entertainment. Fashion innovativeness and technology innovativeness also mediated the relationship between perceived economic risk as well as the purchase intention of smart shoes for healthcare, GPS and entertainment.