Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Short summary

A new Parametric Rectified Linear Unit (PReLU) and a robust initialization method enabled training of extremely deep neural networks, achieving 4.94% top-5 error on ImageNet classification, surpassing human-level performance.

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