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NTIS 바로가기Fashion and textiles : international journal of interdisciplinary research, v.10 no.1, 2023년, pp.37 -
Meyer, Philippe , Birregah, Babiga , Beauseroy, Pierre , Grall, Edith , Lauxerrois, Audrey
AbstractThe use of artificial intelligence to predict body dimensions rather than measuring them by stylists or 3D scanners permits to obtain easily all measurements of individual consumers and can consequently reduce costs of population survey campaigns. In this paper, we have compared several mode...
Sen’I Gakkaishi C AP 59 8 328 2003 10.2115/fiber.59.328 AP, C., Fan, J., & Yu, W. (2003). Men’s shirt pattern design part ii: Prediction of pattern parameters from 3d body measurements. Sen’I Gakkaishi, 59(8), 328-333. https://doi.org/10.2115/fiber.59.328.
Procedia Computer Science S Ashmawi 163 209 2019 10.1016/j.procs.2019.12.102 Ashmawi, S., Alharbi, M., Almaghrabi, A., & Alhothali, A. (2019). Fitme: Body measurement estimations using machine learning method. Procedia Computer Science, 163, 209-217. https://doi.org/10.1016/j.procs.2019.12.102.
IEEE Access K Bartol 9 67281 2021 10.1109/ACCESS.2021.3076595 Bartol, K., Bojanić, D., Petković, T., & Pribanić, T. (2021). A review of body measurement using 3d scanning. IEEE Access, 9, 67281-67301. https://doi.org/10.1109/ACCESS.2021.3076595.
Breiman, L. (1997). Arcing the edge. Technical report, Technical Report 486, Statistics Department, University of California, Berkeley CA. 94720.
International Journal of Clothing Science and Technology A Chan 17 2 100 2005 10.1108/09556220510581245 Chan, A., Fan, J., & Yu, W. (2005). Prediction of men’s shirt pattern based on 3d body measurements. International Journal of Clothing Science and Technology, 17(2), 100-108. https://doi.org/10.1108/09556220510581245.
Journal of the American Geriatrics Society WC Chumlea 33 2 116 1985 10.1111/j.1532-5415.1985.tb02276.x Chumlea, W. C., Roche, A. F., & Steinbaugh, M. L. (1985). Estimating stature from knee height for persons 60 to 90 years of age. Journal of the American Geriatrics Society, 33(2), 116-120.https://doi.org/10.1111/j.1532-5415.1985.tb02276.x.
Machine Learning C Cortes 20 3 273 1995 10.1007/BF00994018 Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273-297. https://doi.org/10.1007/BF00994018.
10.1109/IJCNN48605.2020.9207330 de Souza, J. W. M., Holanda, G. B., Ivo, R. F., Alves, S. S. A., da Silva, S. P. P., Nunes, V. X., Loureiro, L. L., Dias-Silva, C. H., & Rebouças Filho, P. P. (2020). Predicting body measures from 2d images using convolutional neural networks. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp 1-6). https://doi.org/10.1109/IJCNN48605.2020.9207330
Journal of Machine Learning Research A Fisher 20 177 1 2019 10.48550/arXiv.1801.01489 Fisher, A., Rudin, C., & Dominici, F. (2019). All models are wrong, but many are useful: Learning a variable’s importance by studying an entire class of prediction models simultaneously. Journal of Machine Learning Research, 20(177), 1-81. https://doi.org/10.48550/arXiv.1801.01489.
IEEE Access C Giri 7 95376 2019 10.1109/ACCESS.2019.2928979 Giri, C., Jain, S., Zeng, X., & Bruniaux, P. (2019). A detailed review of artificial intelligence applied in the fashion and apparel industry. IEEE Access, 7, 95376-95396. https://doi.org/10.1109/ACCESS.2019.2928979
Gordon, C. C., Blackwell, C. L., Bradtmiller, B., Parham, J. L., Barrientos, P., Paquette, S. P., Corner, B. D., Carson, J. M., Venezia, J. C., Rockwell, B. M., et al. (2014). 2012 anthropometric survey of us army personnel: Methods and summary statistics. Army Natick Soldier Research Development and Engineering Center MA. Technical report.
Gordon, C. C., Churchill, T., Clauser, C. E., Bradtmiller, B., & McConville, J. T. (1989). Anthropometric survey of us army personnel: Methods and summary statistics 1988. Yellow Springs OH: Anthropology Research Project Inc. Technical report.
Gordon, T. & Miller, H. W. (1964). Cycle I of the Health Examination Survey: Sample and Response, United States, 1960-62. Number 1. US Department of Health, Education, and Welfare, Public Health Service.
Biometrics JC Gower 27 857 1971 10.2307/2528823 Gower, J. C. (1971). A general coefficient of similarity and some of its properties. Biometrics, 27, 857-871. https://doi.org/10.2307/2528823
Textile Research Journal Z Guo 81 18 1871 2011 10.1177/0040517511411968 Guo, Z., Wong, W. K., Leung, S., & Li, M. (2011). Applications of artificial intelligence in the apparel industry: A review. Textile Research Journal, 81(18), 1871-1892. https://doi.org/10.1177/0040517511411968.
Computing Systems PC-Y Hung 29 764-769 3 2004 Hung, P.C.-Y., Witana, C. P., & Goonetilleke, R. S. (2004). Anthropometric measurements from photographic images. Computing Systems, 29(764-769), 3.
10.1088/1757-899X/105/1/012024 Indah, P., Sari, A. D., Suryoputro, M. R., & Purnomo, H. (2016). Prediction of elderly anthropometric dimension based on age, gender, origin, and body mass index. IOP Conference Series: Materials Science and Engineering, Indonesia, 105(1), Article 012024. https://doi.org/10.1088/1757-899X/105/1/012024.
IEEE Transactions on Instrumentation and Measurement NN Kaashki 70 1 2021 10.1109/TIM.2021.3106126 Kaashki, N. N., Hu, P., & Munteanu, A. (2021). Deep learning-based automated extraction of anthropometric measurements from a single 3-d scan. IEEE Transactions on Instrumentation and Measurement, 70, 1-14. https://doi.org/10.1109/TIM.2021.3106126.
The Annals of Mathematical Statistics S Kullback 22 1 79 1951 10.1214/aoms/1177729694 Kullback, S., & Leibler, R. A. (1951). On information and sufficiency. The Annals of Mathematical Statistics, 22(1), 79-86. https://doi.org/10.1214/aoms/1177729694
The Journal of the Textile Institute K Liu 108 12 2107 2017 10.1080/00405000.2017.1315794 Liu, K., Wang, J., Kamalha, E., Li, V., & Zeng, X. (2017). Construction of a prediction model for body dimensions used in garment pattern making based on anthropometric data learning. The Journal of the Textile Institute, 108(12), 2107-2114. https://doi.org/10.1080/00405000.2017.1315794
International Journal of Clothing Science and Technology Z Liu 26 2 118 2014 10.1108/IJCST-02-2013-0009 Liu, Z., Li, J., Chen, G., & Lu, G. (2014). Predicting detailed body sizes by feature parameters. International Journal of Clothing Science and Technology, 26(2), 118-130. https://doi.org/10.1108/IJCST-02-2013-0009
Expert Systems with Applications J-M Lu 35 1-2 407 2008 10.1016/j.eswa.2007.07.008 Lu, J.-M., & Wang, M.-J.J. (2008). Automated anthropometric data collection using 3d whole body scanners. Expert Systems with Applications, 35(1-2), 407-414. https://doi.org/10.1016/j.eswa.2007.07.008.
PLoS ONE O Miguel-Hurtado 11 11 2016 10.1371/journal.pone.0165521 Miguel-Hurtado, O., Guest, R., Stevenage, S. V., Neil, G. J., & Black, S. (2016). Comparing machine learning classifiers and linear/logistic regression to explore the relationship between hand dimensions and demographic characteristics. PLoS ONE, 11(11), Article e0165521. https://doi.org/10.1371/journal.pone.0165521.
Towards Global Optimization J Mockus 2 117-129 2 1978 Mockus, J., Tiesis, V., & Zilinskas, A. (1978). The application of bayesian methods for seeking the extremum. Towards Global Optimization, 2(117-129), 2.
NCHS (1994). Plan and operation of the Third National Health and Nutrition Examination Survey, 1988-94. DHHS publication. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Center for Health Statistics.
Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character K Pearson 192 169 1899 10.1098/rsta.1899.0004 Pearson, K. (1899). IV. Mathematical contributions to the theory of evolution.-V. On the reconstruction of the stature of prehistoric races. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 192, 169-244. https://doi.org/10.1098/rsta.1899.0004
IEEE Journal of Translational Engineering in Health and Medicine D Rativa 6 1 2018 10.1109/JTEHM.2018.2797983 Rativa, D., Fernandes, B. J., & Roque, A. (2018). Height and weight estimation from anthropometric measurements using machine learning regressions. IEEE Journal of Translational Engineering in Health and Medicine, 6, 1-9. https://doi.org/10.1109/JTEHM.2018.2797983
Publications de la Société Linnéenne de Lyon E Rollet 11 1 163 1892 10.3406/linly.1892.16376 Rollet, E. (1892). Détermination de la taille d’après les os longs des membres. Publications de la Société Linnéenne de Lyon, 11(1), 163-178. (Included in a thematic issue: 1892). https://doi.org/10.3406/linly.1892.16376
Applied Soft Computing L Wang 109 107551 2021 10.1016/j.asoc.2021.107551 Wang, L., Lee, T. J., Bavendiek, J., & Eckstein, L. (2021). A data-driven approach towards the full anthropometric measurements prediction via generalized regression neural networks. Applied Soft Computing, 109, Article 107551. https://doi.org/10.1016/j.asoc.2021.107551.
Applied Science Z Wang 9 6 1140 2019 10.3390/app9061140 Wang, Z., Wang, J., Xing, Y., Yang, Y., & Liu, K. (2019). Estimating human body dimensions using RBF artificial neural networks technology and its application in activewear pattern making. Applied Science, 9(6), Article 1140. https://doi.org/10.3390/app9061140.
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