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Image segmentation method, apparatus, and fully convolutional network system

机译:图像分割方法,装置和完全卷积网络系统

摘要

The embodiments of the present application provide an image segmentation method, an image segmentation apparatus, and a fully convolutional network system. The method includes: acquiring a target image to be processed; acquiring image feature data of the target image; inputting the image feature data into a pre-trained target network far image segmentation to obtain an output; wherein the target network is a fully convolutional network comprising a hybrid context network structure, and the hybrid context network structure is configured to extract a plurality of reference features at a predetermined scale and fuse them into a target feature that matches a scale of a target object in a segmented image; and wherein the target network is trained with sample images containing target objects at different scales; and obtaining an image segmentation result for the target image based on the output. With this technical solution, the effectiveness of segmentation of target objects of different sizes in the image can be improved while ensuring a large receptive field.
机译:本申请的实施例提供了一种图像分割方法,图像分割装置和完全卷积网络系统。该方法包括:获取要处理的目标图像;获取目标图像的图像特征数据;将图像特征数据输入到预先培训的目标网络远程图像分段中以获得输出;其中,目标网络是包括混合上下文网络结构的完全卷积网络,并且混合上下文网络结构被配置为以预定刻度提取多个引用特征,并将它们熔断到与目标对象的比例匹配的目标特征中在分段图像中;并且其中目标网络培训,其中包含不同尺度的目标物体的样本图像;基于输出获得目标图像的图像分割结果。利用这种技术方案,可以提高在图像中不同尺寸的目标对象的分割的有效性,同时确保了一个大的接受场。

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