新研究设计出能欺骗神经网络的图像，从多角度挑战自动驾驶汽车安全性

We’ve created images that reliably fool neural network classifiers when viewed from varied scales and perspectives. This challenges a claim from last week that self-driving cars would be hard to trick maliciously since they capture images from multiple scales, angles, perspectives, and the like.