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END TO END NETWORK MODEL FOR HIGH RESOLUTION IMAGE SEGMENTATION

机译:用于高分辨率图像分割的端到端网络模型

摘要

The present disclosure provides systems and methods that leverage neural networks for high resolution image segmentation. A computing system can include a processor, a machine-learned image segmentation model comprising a semantic segmentation neural network and an edge refinement neural network, and at least one tangible, non-transitory computer readable medium that stores instructions that cause the processor to perform operations. The operations can include obtaining an image, inputting the image into the semantic segmentation neural network, receiving, as an output of the semantic segmentation neural network, a semantic segmentation mask, inputting at least a portion of the image and at least a portion of the semantic segmentation mask into the edge refinement neural network, and receiving, as an output of the edge refinement neural network, the refined semantic segmentation mask.
机译:本公开提供了利用用于高分辨率图像分割的神经网络的系统和方法。计算系统可以包括处理器,一种机器学习图像分割模型,包括语义分割神经网络和边缘细化神经网络,以及至少一个有形的非暂时性计算机可读介质,其存储导致处理器执行操作的指令。该操作可以包括获得图像,将图像输入到语义分割神经网络,接收作为语义分割神经网络的输出,是语义分割掩模,输入图像的至少一部分和至少一部分语义分割掩模进入边缘细化神经网络,并作为边缘精制神经网络的输出,精制的语义分割掩模。

著录项

  • 公开/公告号EP3625767B1

    专利类型

  • 公开/公告日2021-03-31

    原文格式PDF

  • 申请/专利权人

    申请/专利号EP20170783650

  • 发明设计人 KANAZAWA NORITSUGU;KNAAN YAEL PRITCH;

    申请日2017-09-27

  • 分类号G06T7/12;G06N3/04;G06N3/08;

  • 国家 EP

  • 入库时间 2022-08-24 18:00:28

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