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METHOD AND SYSTEM FOR PREDICTING GARMENT ATTRIBUTES USING DEEP LEARNING

机译:基于深度学习的服装属性预测方法和系统

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:提供了一种使用深度学习技术预测服装或配件属性的计算机实现的方法,该方法包括以下步骤:(i)接收和存储一个或多个数字图像数据集,包括服装或配件的图像; (ii)通过配置深度神经网络模型来预测(a)多类离散属性,使用存储的一个或多个数字图像数据集训练用于服装或配件属性识别的深度模型; (b)二进制离散属性,和(c)连续属性,(iii)接收服装或配件的一个或多个数字图像,以及(iv)从一个或多个接收的数字图像中提取服装或配件的属性使用训练有素的深度模型来识别服装或配饰属性。还提供了相关的系统。

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