Nathan Inkawhich
3 papers in the PaperMetrix corpus
Papers by this author
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Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
2020 · arXiv (Cornell University)
We consider the blackbox transfer-based targeted adversarial attack threat model in the realm of deep neural network (DNN) image classifiers. Rather than focusing on crossing decision boundaries at the output layer of the source model, …
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Fine-grained Out-of-Distribution Detection with Mixup Outlier Exposure.
2021 · arXiv (Cornell University)
Enabling out-of-distribution (OOD) detection for DNNs is critical for their safe and reliable operation in the open world. Unfortunately, current works in both methodology and evaluation focus on rather contrived detection problems, and only consider …
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Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained Environments
2023 · 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Many real-world scenarios in which DNN-based recognition systems are deployed have inherently fine-grained attributes (e.g., bird-species recognition, medical image classification). In addition to achieving reliable accuracy, a critical subtask for these models is to detect …