تقرير
Segmentation task for fashion and apparel
| العنوان: | Segmentation task for fashion and apparel |
|---|---|
| المؤلفون: | Castro, Hassler, Ramirez, Mariana |
| سنة النشر: | 2020 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning |
| الوصف: | The Fashion Industry is a strong and important industry in the global economy. Globalization has brought fast fashion, quick shifting consumer shopping preferences, more competition, and abundance in fashion shops and retailers, making it more difficult for professionals in the fashion industry to keep track of what fashion items people wear and how they combine them. This paper solves this problem by implementing several Deep Learning Architectures using the iMaterialist dataset consisting of 45,000 images with 46 different clothing and apparel categories. Comment: 8 pages, 7 figures. To appear as one of the projects associated with the advance machine learning class at Universidad EAFIT, June 2019. Medellin, Colombia |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2006.11375 |
| رقم الأكسشن: | edsarx.2006.11375 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |