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Multi-task learning incorporating dependencies method for bionic eye's face attribute recognition

机译:多任务学习掺入仿生眼的脸部属性识别的依赖性方法

摘要

The application discloses a multi-task learning incorporating dependencies method for bionic eye's face attribute recognition, which is as follows: Determine the first face attribute and the second face attribute for attribute recognition of facial image. Obtain the first recognition task branch and the second recognition task branch. Establish the task dependency between the first recognition task branch and the second recognition task branch to obtain the first transformed face attribute fully connected layer related to the second face attribute. and the second transformed face attribute fully connected layer related to the first face attribute. Feed the first transformed face attribute fully connected layer into the prediction layer to predict the first face attribute of facial image. And feed the second transformed face attribute fully connected layer into the prediction layer to predict the second face attribute of facial image. The multi-task learning incorporating dependencies method for bionic eye's face attribute recognition will be obtained according to the above steps.
机译:该应用公开了一种结合仿生眼的面部属性识别依赖性方法的多任务学习,这如下:确定面部图像的属性识别的第一面部属性和第二面属性。获取第一识别任务分支和第二个识别任务分支。在第一识别任务分支和第二识别任务分支之间建立任务依赖性,以获得与第二面属性相关的第一变换的面部属性完全连接层。和与第一面属性相关的完全连接的层的第二变换的面部属性。将第一变换的面部属性完全连接的层馈送到预测层中以预测面部图像的第一面属性。并将第二变换的面部属性完全连接层馈送到预测层中以预测面部图像的第二面属性。将依赖于仿生眼的面部属性识别的依赖性方法的多任务学习将根据上述步骤获得。

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