Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
Paper summary ## Task Add '**rejection**' output to an existing classification model with softmax layer. ## Method 1. Choose some threshold $\delta$ and temperature $T$ 2. Add a perturbation to the input x (eq 2), let $\tilde x = x - \epsilon \text{sign}(-\nabla_x \log S_{\hat y}(x;T))$ 3. If $p(\tilde x;T)\le \delta$, rejects 4. If not, return the output of the original classifier $p(\tilde x;T)$ is the max prob with temperature scailing for input $\tilde x$ $\delta$ and $T$ are manually chosen.
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Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
Shiyu Liang and Yixuan Li and R. Srikant
arXiv e-Print archive - 2017 via Local arXiv
Keywords: cs.LG, stat.ML

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Summary by elbaro 4 months ago
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