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Sphereface
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Spherenet是2017年提出的使用改进的softamax在人脸识别领域进行的一项创新。他提出了angular softmax loss用来改进原来的softmax loss，在large margin softmax loss的基础上增加了||W||=1以及b=0的两个限制条件，使得预测结果仅仅取决于W和x之间的角度。他的应用场景是在开集环境下的，该论文也主要解决了这一任务，使得在特定的测度空间下，能够尽可能的满足最大类内距离小于不同类的最小类间距离，该论文使得特征更加具有可判别性。

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