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Method and system for predicting garment attributes using deep learning

机译:使用深度学习预测服装属性的方法和系统

摘要

There is provided a computer implemented method for predicting garment or accessory attributes using deep learning techniques, comprising the steps of: (i) receiving and storing one or more digital image datasets including images of garments or accessories; (ii) training a deep model for garment or accessory attribute identification, using the stored one or more digital image datasets, by configuring a deep neural network model to predict (a) multiple-class discrete attributes; (b) binary discrete attributes, and (c) continuous attributes, (iii) receiving one or more digital images of a garment or an accessory, and (iv) extracting attributes of the garment or the accessory from the one or more received digital images using the trained deep model for garment or accessory attribute identification. A related system is also provided.
机译:提供了一种用于使用深度学习技术预测服装或附件属性的计算机实现的方法,包括以下步骤:(i)接收和存储包括服装或附件的图像的一个或多个数字图像数据集; (ii)通过配置深神经网络模型来预测(a)多级离散属性,训练衣服或附件属性识别的深层模型,用于使用存储的一个或多个数字图像数据集来预测(a)多级离散属性; (b)二进制离散属性,(c)连续属性,(iii)接收服装或附件的一个或多个数字图像,(iv)从一个或多个接收的数字图像中提取衣服的属性或附件使用训练有素的衣训或附件属性识别。还提供了相关系统。

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