Relevant bibliographies by topics / Personalized Fashion

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Personalized Fashion'

Author: Grafiati
Published: 6 June 2025
Last updated: 25 July 2025

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Journal articles on the topic "Personalized Fashion"

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Vattikonda, Navya, Anuj Kumar Gupta, Achuthananda Reddy Polu, Bhumeka Narra, and Dheeraj Varun Kumar Reddy Buddula. "Leveraging Deep Learning for Personalized Fashion Recommendations Using Fashion MNIST." International Journal of Multidisciplinary Research in Science and Business 1, no. 07 (2024): 54–77. https://doi.org/10.63665/ijmrsb.v1i07.08.

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People are particularly consciousof their clothing choices since fashion has a big influence on daily life. Large populations are usually recommended fashion goods and trends by specialists via a manual, curated process. On the other hand, e-commerce websites greatly benefit from automatic, personalized recommendation systems, which are becoming more popular. This study introduces a deep learning-based framework for personalized fashion recommendation, utilizing the Fashion-MNIST dataset as the primary data source. The dataset was dividedinto training and testing sets in a 70:30 ratio to ensur
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Vattikonda, Navya, Anuj Kumar Gupta, Achuthananda Reddy Polu, Bhumeka Narra, and Dheeraj Varun Kumar Reddy Buddula. "Leveraging Deep Learning for Personalized Fashion Recommendations Using Fashion MNIST." International Journal of Multidisciplinary Research in Science and Business 1, no. 07 (2024): 54–77. https://doi.org/10.63665/ijmrsb.v1i01.08.

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People are particularly consciousof their clothing choices since fashion has a big influence on daily life. Large populations are usually recommended fashion goods and trends by specialists via a manual, curated process. On the other hand, e-commerce websites greatly benefit from automatic, personalized recommendation systems, which are becoming more popular. This study introduces a deep learning-based framework for personalized fashion recommendation, utilizing the Fashion-MNIST dataset as the primary data source. The dataset was dividedinto training and testing sets in a 70:30 ratio to ensur
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Navya, Vattikonda. "Leveraging Deep Learning for Personalized Fashion Recommendations Using Fashion MNIST." International Journal of Multidisciplinary Research in Science and Business 01, no. 07 (2025): 1–8. https://doi.org/10.5281/zenodo.15130896.

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—People are particularly conscious of their clothingchoices since fashion has a big influence on daily life. Largepopulations are usually recommended fashion goods and trendsby specialists via a manual, curated process. On the other hand,e-commerce websites greatly benefit from automatic,personalized recommendation systems, which are becomingmore popular. This study introduces a deep learning-basedframework for personalized fashion recommendation, utilizingthe Fashion-MNIST dataset as the primary data source. Thedataset was divided into training and testing sets in a 70:30 ratioto ensure
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Navya, Vattikonda Anuj Kumar Gupta Achuthananda Reddy Polu Bhumeka Narra and Dheeraj Varun Kumar Reddy Buddula. "Leveraging Deep Learning for Personalized Fashion Recommendations Using Fashion MNIST." International Journal of Multidisciplinary Research in Science and Business 1, no. 7 (2025): 54–77. https://doi.org/10.5281/zenodo.15349661.

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People are particularly conscious of their clothing choices since fashion has a biginfluence on daily life. Large populations are usually recommended fashion goodsand trends by specialists via a manual, curated process. On the other hand, ecommerce websites greatly benefit from automatic, personalized recommendationsystems, which are becoming more popular. This study introduces a deep learningbased framework for personalized fashion recommendation, utilizing the FashionMNIST dataset as the primary data source. The dataset was divided into trainingand testing sets in a 70:30 ratio to ensure rob
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Vattikonda, Navya, Anuj Kumar Gupta, Achuthananda Reddy Polu, Bhumeka Narra, Dheeraj Varun Kumar Reddy Buddula, and Hari Hara Sudheer Patchipulusu. "Leveraging Deep Learning for Personalized Fashion Recommendations Using Fashion MNIST." International Journal of Emerging Trends in Computer Science and Information Technology 6 (2025): 36–46. https://doi.org/10.63282/3050-9246.ijetcsit-v6i2p105.

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Sangkhathat, Surasak. "‘Personalized’ or ‘Precision’, Future or Fashion." Journal of Health Science and Medical Research 36, no. 3 (2018): 165. http://dx.doi.org/10.31584/jhsmr.2018.36.3.13.

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M Vinitha, Dr.B. Nagarajanaik, Mallikarjuna Nandi, C Naga Sri Charan, and K Priyanka. "Fashion Recommendation System." International Research Journal on Advanced Engineering Hub (IRJAEH) 2, no. 05 (2024): 1243–47. http://dx.doi.org/10.47392/irjaeh.2024.0171.

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Fashion recommendation systems have become increasingly essential in the e-commerce industry, providing personalized outfit suggestions to users, enhancing their shopping experience, and boosting sales. This paper presents a novel approach to fashion recommendation by combining machine learning and deep learning techniques. We leverage a comprehensive dataset of user preferences and fashion items to create a robust recommendation system. Our approach first employs collaborative filtering and matrix factorization methods to establish user-item interactions. Subsequently, deep learning models, s
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Thakur, Swapnil, Shreyas Dixit, and Prof Rahul Dagade. "Review of Personalized Outfit Recommender." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 11 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem26956.

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In the age of looking good, we come across that one question everyday; What should I wear to look good today?. The question span a broad variety of topics, such as what am I missing in wardrobe? what is the current trend? will this suit my skin tone? will this work in current climate. the integration of technology and clothing has revolutionized the way individuals perceive and choose their outfits. This study presents a cutting-edge outfit recommendation system that combines the analysis of user skin tones, real-time weather data, and advanced machine learning algorithms. The system utilizes
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Sun, Kexin, Peng Zhang, Jie Zhang, Jing Tao, and Kexin Yuan. "PFNet: Attribute-aware personalized fashion editing with explainable fashion compatibility analysis." Information Processing & Management 61, no. 1 (2024): 103540. http://dx.doi.org/10.1016/j.ipm.2023.103540.

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Paik, Hyo Yon, and Jee Hyun Lee. "Personalized Fashion Design using Data Visualization method." Journal of the Korean Society of Costume 67, no. 5 (2017): 17–30. http://dx.doi.org/10.7233/jksc.2017.67.5.017.

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Dissertations / Theses on the topic "Personalized Fashion"

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Wang, Lichuan. "Contribution to development of an intelligent system for supporting personalized fashion design." Thesis, Lille 1, 2012. http://www.theses.fr/2012LIL10033/document.

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La mass customisation a été appliquée au marché de grande consommation de vêtements depuis plus de 20 ans. Pourtant, les travaux concernés se focalisent essentiellement sur le prototypage virtuel par utilisation des outils de CAO. Le stylisme et le marketing n’ont pas été étudiés de façon systématique. Dans le cadre de ma thèse doctorale, nous proposons un système d’aide à la décision orienté vers les styles afin de fournir des conseils aux créateurs. Dans ce système, nous caractérisons, d’abord, les perceptions de créateurs et de consommateurs sur les morphotypes. Deux expériences ont été eff
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Urrea, Inmaculada. "La Construcción de la marca personal de Coco Chanel a través de sus fotografías: su aportación a la creación de la mujer moderna." Doctoral thesis, Universitat Pompeu Fabra, 2016. http://hdl.handle.net/10803/385858.

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El objetivo principal de la presente tesis es investigar sobre cómo Coco Chanel, la mujer más importante de la creación de moda femenina y una de las mujeres más importantes del siglo XX, construyó su marca personal a través de sus retratos. Para ello se investiga en dos direcciones, una, la marca en todas sus dimensiones, desde la comercial a la antropomorfa, pasando por su relación con la emoción y el recuerdo, y los modelos de construcción de marca personal. Otra, la semiótica aplicada al campo visual para desentrañar todos los significados asociados al corpus fotográfico de Chanel analizad
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Chiu, Yen-Lin, and 邱彥霖. "The Personalized Recommender System for Kiosk in Fast Fashion Industry." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/34596101502354736273.

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碩士<br>國立交通大學<br>交通運輸研究所<br>98<br>Because of the rapid development of information technology, many clothing enterprises try to implement the concept of smart store. These enterprises introduce a number of technology applications to their physical stores. In addition, these enterprises take “Fast Fashion” as their business strategy so that their clothing products would be diversity and have a quite short life cycle. The Kiosk is a new facility in physical clothing store and there is no recommendation system for Kiosk. The traditional recommendation system is not an efficient way for Kiosk becaus
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Books on the topic "Personalized Fashion"

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Hernandez, Helen. Manual de personalidad e imagen: Brilla con luz propia. Editorial Pax México, 2007.

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Abling, Bina. Fashion Sketchbook. Bloomsbury Publishing Plc, 2023. http://dx.doi.org/10.5040/9781501387920.

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Learn how to draw fashion images that communicate design ideas and details. With more than 3,000 color illustrations and updated instructions, the book shows you how to draw women, men, and children, pose the figure, develop the fashion head and face, sketch accessories, add garment details, and prepare flats and specs. Learn more advanced techniques for rendering color, fabrics, and embellishments, from houndstooth and velvet to feathers and fringe. Bina Abling’s detailed, easy-to-follow lessons have clear diagrams and runway photographs to help you develop your drawing skills. New to this Ed
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Art, Black. Molly: Personalized Edgy Fashion Themed Journal with Lined Pages. Independently Published, 2018.

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Art, Black. Naomi: Personalized Edgy Fashion Themed Journal with Lined Pages. Independently Published, 2018.

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Harlacher, Petra. Personalized Fashion Teacher Gift: Beautiful Appreciation Gift for Women. Independently Published, 2021.

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Art, Black. Peyton: Personalized Edgy Fashion Themed Journal with Lined Pages. Independently Published, 2018.

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Ulasewicz, Connie, and Janet Hethorn. Sustainable Fashion. 3rd ed. Bloomsbury Publishing Inc, 2023. http://dx.doi.org/10.5040/9781501385650.

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Sustainable Fashion: Take Action, Third Edition presents a fresh exploration of practices that are underway in design and production within the fashion industry and the possibilities for future directions that can be taken now. This book focuses on innovative action needed to achieve the goal of creating healthier environments, reducing climate change, and improving the well-being of all people as they choose and wear clothing. This third edition continues to delve into the role that fashion plays in a sustainable future, through the interconnected model of “Connecting with People, Processes,
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Rousso, Chelsea, and Nancy Kaplan Ostroff. Fashion Forward. 3rd ed. Bloomsbury Publishing Inc, 2024. http://dx.doi.org/10.5040/9781501374333.

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Fashion Forward, Third Edition demystifies the ever-changing career of fashion forecasting. It provides an overview of fashion forecasting theories and concepts, then gives a step-by-step guide to creating and presenting a forecast. The events of the 21st century have turned fashion on its head, forcing the industry to adapt to global pandemics, protests, and shifts in political power, and this book teaches readers to think critically about how the impacts of these events affect fashion trends. Different fashion consumers have different needs, and Fashion Forward considers a diverse range of c
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Ellinwood, Janice Greenberg. Fashion by Design. 2nd ed. Bloomsbury Publishing Plc, 2022. http://dx.doi.org/10.5040/9781501359439.

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Fashion by Design, Second Edition, explains how the elements and principles of design relate to fashion, based on the philosophy of the Bauhaus Experiment of the 1920s and 1930s, which is the foundation for art education in the United States. The book is structured into three parts: the stages of the design process (inspiration, identification, conceptualization, exploration/refinement, definition/modeling, communication, and production); physical elements (such as line, shape, form, space, texture, light, pattern, color, and value); and theoretical principles (like balance, emphasis, rhythm,
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Jalal Coloring Jalal Coloring Books. Personalized Wedding Coloring Book for Adults: Adult Coloring Book with Beautiful Wedding Dresses , Fashion and Features Wedding Fashion Illustrations. Independently Published, 2022.

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Book chapters on the topic "Personalized Fashion"

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Plumbaum, Till, and Benjamin Kille. "Personalized Fashion Advice." In Smart Information Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14178-7_8.

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Iliukovich-Strakovskaia, Anna, Victoria Tsvetkova, Emeli Dral, and Alexey Dral. "Non-personalized Fashion Outfit Recommendations." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77700-9_5.

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Trakulwaranont, Donnaphat, Marc A. Kastner, and Shin’ichi Satoh. "Personalized Fashion Recommendation Using Pairwise Attention." In MultiMedia Modeling. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98355-0_19.

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Guan, Weili, Xuemeng Song, Xiaojun Chang, and Liqiang Nie. "Heterogeneous Graph Learning for Personalized OCM." In Graph Learning for Fashion Compatibility Modeling. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18817-6_6.

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Xu, Shihui, Jingyi Yuan, Xitong Sun, et al. "Augmented Reality Fashion Show Using Personalized 3D Human Models." In Human Interface and the Management of Information. Designing Information. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50020-7_31.

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Xian, Dan, Shaozan Cui, Bo Wang, and Lishuai Cui. "H&M Personalized Fashion Product Recommendation Using LightgbmRanker." In Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023). Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-198-2_23.

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Arunkumar, S., Gerard Deepak, J. Sheeba Priyadarshini, and A. Santhanavijayan. "PMFRO: Personalized Men’s Fashion Recommendation Using Dynamic Ontological Models." In Hybrid Intelligent Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_9.

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Ramampiaro, Heri, Helge Langseth, Thomas Almenningen, Herman Schistad, Martin Havig, and Hai Thanh Nguyen. "New Ideas in Ranking for Personalized Fashion Recommender Systems." In Business and Consumer Analytics: New Ideas. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-06222-4_25.

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Papachristou, Evridiki, Zoe Dimou, Margarita Grammatikopoulou, Lampros Mpaltadoros, and Thanos G. Stavropoulos. "Personalized Fashion On-Demand and e-Fashion Business Models: A User Survey in Greece." In Management and Industrial Engineering. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98124-2_4.

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Bollacker, Kurt, Natalia Díaz-Rodríguez, and Xian Li. "Extending Knowledge Graphs with Subjective Influence Networks for Personalized Fashion." In Designing Cognitive Cities. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00317-3_9.

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Conference papers on the topic "Personalized Fashion"

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Shoeb, Aamir, Mohammed Hamza Ali, Md Mahmood Ali, and Mohammad Sanaullah Qaseem. "PFRS: Personalized Fashion Recommendation System Using EfficientNet." In 2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT). IEEE, 2024. https://doi.org/10.1109/3ict64318.2024.10824272.

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Kumar, C. Siva, M. P. Deeraj, K. N. Harsha Vardhan, K. Amulya, and K. Govardhan. "Fashionista a Personalized Fashion and Style Recommendation System with Machine Learning Insights." In 2024 10th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2024. http://dx.doi.org/10.1109/icaccs60874.2024.10717000.

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Yu, Cong, Yang Hu, Yan Chen, and Bing Zeng. "Personalized Fashion Design." In 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2019. http://dx.doi.org/10.1109/iccv.2019.00914.

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Stan, Cristiana, and Irina Mocanu. "An Intelligent Personalized Fashion Recommendation System." In 2019 22nd International Conference on Control Systems and Computer Science (CSCS). IEEE, 2019. http://dx.doi.org/10.1109/cscs.2019.00042.

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Gray, Chester, Meghan Beattie, Helena Belay, Sarah Hill, and Nicolette Lerch. "Personalized online search for fashion products." In 2015 Systems and Information Engineering Design Symposium. IEEE, 2015. http://dx.doi.org/10.1109/sieds.2015.7117018.

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Tu, Qingqing, and Le Dong. "An Intelligent Personalized Fashion Recommendation System." In 2010 International Conference on Communications, Circuits and Systems (ICCCAS). IEEE, 2010. http://dx.doi.org/10.1109/icccas.2010.5581949.

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Lu, Zhi, Yang Hu, Yunchao Jiang, Yan Chen, and Bing Zeng. "Learning Binary Code for Personalized Fashion Recommendation." In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2019. http://dx.doi.org/10.1109/cvpr.2019.01081.

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Li, Xingchen, Xiang Wang, Xiangnan He, Long Chen, Jun Xiao, and Tat-Seng Chua. "Hierarchical Fashion Graph Network for Personalized Outfit Recommendation." In SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval. ACM, 2020. http://dx.doi.org/10.1145/3397271.3401080.

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Zeng, X., L. Koehl, L. Wang, and Y. Chen. "An intelligent recommender system for personalized fashion design." In 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS). IEEE, 2013. http://dx.doi.org/10.1109/ifsa-nafips.2013.6608496.

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Ding, Yujuan, P. Y. Mok, Yi Bin, Xun Yang, and Zhiyong Cheng. "Modeling Multi-Relational Connectivity for Personalized Fashion Matching." In MM '23: The 31st ACM International Conference on Multimedia. ACM, 2023. http://dx.doi.org/10.1145/3581783.3612583.

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