• Fashion & Textile Research Journal
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• v.23 no.6
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• pp.709-725
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• 2021

The study focused on the design features of Chanel and Fendi, directed by Carl Lagerfeld, creative director of Chanel and Fendi until his recent death. The range of the study was from the 2017 S/S Collection to the 2019 F/W Collection, which collected a total of 767 fashion photographs, including 483 Chanel, 284 Fendi, with tops, bottoms and dresses at VOGUE (https://www.vogue.com). According to the data analysis criteria organized based on prior research and related literature, it was classified in the order of form, color, material, pattern, decoration, fashion image, item and coordination, and content analysis was conducted based on statistical analysis. Overall, the design characteristics of the Chanel collection, directed by Karl Lagerfeld, were rectangle form, tone in tone coloring, combination of identical materials, geometric patterns, and classical images as the main design characteristics of the Chanel collection. The design characteristics shown in the Fendi collection directed by Karl Lagerfeld were rectangle form, tone in tone coloration, hard material combination, abstract pattern, and total coordination. Comparing the design features of Chanel and Fendi, directed by Karl Lagerfeld, is as follows. Chanel and Fendi's designs show a lot of rectangle form, tone-in-tone colors, hard-materials and combination of the same material.

• Korean Institute of Interior Design Journal
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• v.16 no.2 s.61
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• pp.209-216
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• 2007

Some may call Peter Marine as 'an ego-less architect', or 'palace maker' due to his designs or attitudes that appearantly please world's most well known clients. However, his eclectic taste and artistic expressions combined with his minimal and abstract architectural approaches are being recognized in many places globally, especially in many fashion brand stores such as Channel, Louis Vuitton, Christian Dior, and Fendi. Born and educated in U.S., Peter Marino designs are influenced by two most famous designers of our modern art history Andy Warhol and Jean-Micheal Franks, that are obvious in his traditionally modern French style designs and abstract expressions. The current study introduces Peter Marine designs through analyses of Channel and Louis Vuitton. The objectives are to understand the designer and find patterns in his brand store designs that has made him now one of the most famous fashion store designers. Educational, social, and personal interest were found to strongly form his design characteristics and four main characteristics were identified by the researcher that are use of LED lightings, emphasis on vortical circulations, graphical application of brand identities, and repetition of simple geometric forms.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.1-14
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• 2016

This study analyzes consumers' preference trend, positive and negative factors in regards to luxury brands by researching changes in the consumer awareness of luxury brands, preference trends and psychological awareness based on big data to suggest a creative business strategy for corporations that can help Korean brands enter global luxury brand markets. The study results are as follows. Preferred items (consumer) psychology, positive awareness and negative awareness were derived based on the last five years of social big data on Korean consumers' preferred brands. First, the Korean consumers' preferred brands for the recent five years indicated that Dolce & Gabbana (2013), ESCADA (2012), Gucci (2011, 2009) and Chanel (2010) were most preferred and Prada, Louis Vuitton, Hermes, Burberry, Fendi, Givenchy and Dior were also shown to be preferred brands. Second, bags (such as shoulder bags) were shown to be the most preferred items for luxury brand items that consumers wished to own. Third, it was analyzed that keywords for consumer psychology in regards to luxury brands included: diverse, new, outstanding, overwhelming, luxurious, glamorous, worldwide, famous, success and good. Fourth, consumers' positive awareness regarding luxury brands included: diverse, luxury, famous, outstanding, perfect, bright and luxurious. Fifth, negative awareness included: price factors of expensive, high price and excessive as well as factors to be improved upon such as old, bland, flashy, crude, unfriendly and fake.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.1
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• pp.12-23
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• 2008

The purpose of this study is in planning clothing and bag design and VMD. For this purpose, the pret-a-porter fashion collection is divided into the following sectors: brands, years, and seasons, focusing on the design elements. The results of this study are as follows: 1. It is these three ways that determine the relevance of clothing and bag design planning. first, we have analyzed design properties analogously with one design element, like Louis Vuitton. Second, we considered design properties analogously with two design elements, like Chanel, Gucci, Prada. Third, we examined design properties analogously with three design elements, like Christian dior, Fendi, Etro. 2. The comparison of clothing and bag design properties year by year shows that they were mainly designed with an analogous aspect with pattern and decoration. 3. Clothing does well to match a bag between analogous design properties of design elements to express similarity coordination and between contrast design properties of design elements to express plus one coordination or crossover coordination. 4. The aspect of coordination of clothing and bags year by year is different period. This is because of clothing and bag design's change according fashion trend. 5. S/S coordination of clothing and bags is effective to present plus one coordination or crossover coordination. And F/W coordination of clothing and bags is effective to present similarity in coordination.

• Journal of Fashion Business
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• v.27 no.6
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• pp.66-84
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• 2023

Handbags are a part of fashion and while their significance and value are increasing, research on this topic is lacking. This study defines handbags and categorizes the materials used for making handbags, sewing methods, expression techniques, and terminologies related to accessories. A total of 1,743 handbags that were released from the Spring 2020 to Fall 2023, Ready-to-Wear collections by 8 selected brands (Hermes, Dior, Fendi, Chanel, Louis Vuitton, Prada, Gucci, and Alexander McQueen), were analyzed. Out of these, 732 unique designs, excluding those with only color variations, were studied. The most common sewing methods were 'Cut, sewing, and edge painting', 'Cylinder arm sewing', 'Cut, edge painting, and sewing', and 'Inverted seam', in that order. Slim strap designs primarily used the 'Cut, sewing, and edge painting' method, whereas the body, especially with narrow and hard leather, was best suited for the 'Cylinder arm sewing machine'. For expression techniques, the most frequently used methods were 'Quilting', 'Metal Eyelet', 'Embossing', 'Printing', 'Punching', and 'Weaving', respectively. The characteristics of each brand's production methods, expression techniques, and accessories were as follows: First, the exposure of logos and monograms is prominent. Unlike clothing, handbags often prominently feature the brand's logo or monogram. Second, signature quilting is a prominent feature. Quilting effectively conveys the brand's signature style, providing cushioning, volume, and pattern effects. Third, sustainable development is a growing trend. Brands are increasingly applying eco-friendly and socially responsible designs.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.10
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• pp.1487-1496
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• 2008

The purpose of this study is to provide guidance to plan bag design with an analysis of design properties of bags of famous overseas brands in a pret-a-porter fashion collection. For this purpose, the pret-a-porter fashion collection from 2001 S/S to 2005 F/W is divided into the following sectors: brands, years, and seasons, focusing on the design elements. The reference for the actual study was 773 pictures of bags that were collected of Chanel, Louis Vuitton, Gucci, Christian Dior, Prada, Fendi and Etro collections. The results of this study are as follows. With regard to the character of the bag design classified by brand, the design property was embossed with all design elements. Therefore, we can use design elements to express design property, like bag design of famous overseas brands. With regard to the changes of bag design year by year, it was changed with almost all of the design elements. Therefore, it is noted that bag design do well to reflect the fashion trends of the year with almost all design elements. With regard to design properties of seasonal bags, bag design properties which are popular in the S/S season are circle form, small size, lively colors and so on. On the other hand, bag design properties which are popular in the F/W season are common form, large size, quiet colors and so on. Therefore, it is noted that bag design do well to reflect the seasonal trends.

• Journal of Fashion Business
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• v.23 no.1
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• pp.145-162
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• 2019

This study reviewed photos of women's jackets shown at Milano Collections from 2013 S/S to 2017 F/W to identify the variations and trends in their structural components and design elements with respect to year and season. 576 photos, which consist of 276 S/S jackets and 300 F/W jackets by renowned Italian luxury fashion brands; Giorgio Armani, Gucci, Fendi, Max Mara and Jil Sander, were analyzed. Some of the highlighted findings are as follows; in the structural aspects, the H-line silhouette, below waist to hip line length, natural shoulder line and single button closure were the most frequently appearing components among all the jackets. For the design elements, the largest number of jackets was made of woven fabric in single color, while fur was mostly used in F/W seasons for its warmth, heaviness and bulky appearance. From the results, it was established that variations were made to the jacket components and design elements to the extent that they convey predominant jacket styles with a certain level of practicality and performance. However, the study also found that some of the jackets demonstrated design diversity and innovation by adopting daring styles, bold materials and colors. As the findings of this study identified the variations and trends in women's jacket components in recent years, they can be applied towards developing high end women's jackets to meet the demands and distinctive needs of luxury clothing buyers and distributors.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.