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Utilizing deep learning for automatic digital image segmentation and stylization

机译:利用深度学习进行自动数字图像分割和样式化

摘要

Systems and methods are disclosed for segregating target individuals represented in a probe digital image from background pixels in the probe digital image. In particular, in one or more embodiments, the disclosed systems and methods train a neural network based on two or more of training position channels, training shape input channels, training color channels, or training object data. Moreover, in one or more embodiments, the disclosed systems and methods utilize the trained neural network to select a target individual in a probe digital image. Specifically, in one or more embodiments, the disclosed systems and methods generate position channels, training shape input channels, and color channels corresponding the probe digital image, and utilize the generated channels in conjunction with the trained neural network to select the target individual.
机译:公开了用于将探针数字图像中表示的目标个体与探针数字图像中的背景像素分离的系统和方法。特别地,在一个或多个实施例中,所公开的系统和方法基于训练位置通道,训练形状输入通道,训练颜色通道或训练对象数据中的两个或更多个来训练神经网络。此外,在一个或多个实施例中,公开的系统和方法利用训练的神经网络来选择探针数字图像中的目标个体。具体地,在一个或多个实施例中,所公开的系统和方法生成对应于探针数字图像的位置通道,训练形状输入通道和颜色通道,并且结合所训练的神经网络利用所生成的通道来选择目标个体。

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