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GRAPHITE: Generating Automatic Physical Examples for Machine-Learning Attacks on Computer Vision Systems.

, , , , , and . EuroS&P, page 664-683. IEEE, (2022)

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Understanding the Impact of Compression on Feature Detection and Matching in Computer Vision., , , and . ISM, page 457-462. IEEE Computer Society, (2016)Query-Efficient Physical Hard-Label Attacks on Deep Learning Visual Classification., , , , , and . CoRR, (2020)Concept-based Explanations for Out-of-Distribution Detectors., , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 5817-5837. PMLR, (2023)ISIFT: extracting incremental results from SIFT., , and . MMSys, page 195-203. ACM, (2018)Robot-Assisted Feeding: Generalizing Skewering Strategies Across Food Items on a Plate., , , , , , , and . ISRR, volume 20 of Springer Proceedings in Advanced Robotics, page 427-442. Springer, (2019)D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles., , , , , and . WACV, page 3800-3810. IEEE, (2024)Leveraging Image Processing Techniques to Thwart Adversarial Attacks in Image Classification., , , and . ISM, page 184-191. IEEE, (2019)Stateful Defenses for Machine Learning Models Are Not Yet Secure Against Black-box Attacks., , , , , and . CCS, page 786-800. ACM, (2023)Essential Features: Reducing the Attack Surface of Adversarial Perturbations with Robust Content-Aware Image Preprocessing., , and . CoRR, (2020)GRAPHITE: Generating Automatic Physical Examples for Machine-Learning Attacks on Computer Vision Systems., , , , , and . EuroS&P, page 664-683. IEEE, (2022)