首页> 外国专利> ITERATIVELY APPLYING NEURAL NETWORKS TO AUTOMATICALLY IDENTIFY PIXELS OF SALIENT OBJECTS PORTRAYED IN DIGITAL IMAGES

ITERATIVELY APPLYING NEURAL NETWORKS TO AUTOMATICALLY IDENTIFY PIXELS OF SALIENT OBJECTS PORTRAYED IN DIGITAL IMAGES

机译:迭代地应用神经网络来自动识别刻画在图像中的显着对象的像素

摘要

The present disclosure relates to systems, method, and computer readable media that iteratively apply a neural network to a digital image at a reduced resolution to automatically identify pixels of salient objects portrayed within the digital image. For example, the disclosed systems can generate a reduced-resolution digital image from an input digital image and apply a neural network to identify a region corresponding to a salient object. The disclosed systems can then iteratively apply the neural network to additional reduced-resolution digital images (based on the identified region) to generate one or more reduced-resolution segmentation maps that roughly indicate pixels of the salient object. In addition, the systems described herein can perform post-processing based on the reduced-resolution segmentation map(s) and the input digital image to accurately determine pixels that correspond to the salient object.
机译:本公开涉及系统,方法和计算机可读介质,其以降低的分辨率迭代地将神经网络应用于数字图像以自动识别在数字图像内描绘的显着物体的像素。例如,公开的系统可以从输入的数字图像生成分辨率降低的数字图像,并应用神经网络来识别与显着物体相对应的区域。然后,所公开的系统可以将神经网络迭代地应用于附加的分辨率降低的数字图像(基于所识别的区域),以生成一个或多个分辨率降低的分割图,其大致指示出显着物体的像素。另外,本文描述的系统可以基于降低分辨率的分割图和输入数字图像执行后处理,以准确地确定与显着对象相对应的像素。

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