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May, 2022
人类和机器对极端图像变换下的物体识别的鲁棒性
Robustness of Humans and Machines on Object Recognition with Extreme Image Transformations
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Dakarai Crowder, Girik Malik
TL;DR
该论文探讨了神经网络架构在解决视觉任务时存在的局限性,与人类学习抽象概念的策略不同。研究利用一组新的图像转换方法,对人类和网络在对象识别任务上进行了评估,发现常见网络的性能迅速下降,而人类能够以高精度识别对象。
Abstract
Recent
neural network architectures
have claimed to explain data from the
human visual cortex
. Their demonstrated performance is however still limited by the dependence on exploiting low-level features for solvin
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