Machine Learning for Security and Security for Machine Learning with Nicole Nichols - TWiML Talk #252
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Exploring Object Recognition Vulnerabilities
This chapter examines an experimental setup aimed at assessing the vulnerabilities of object recognition systems using physical toys and the CIFAR-10 dataset. It reveals how lighting variations and added visual inputs significantly impact classification accuracy, raising concerns about the robustness of machine learning models. The discussion stresses the necessity for improved datasets and evaluation methods to enhance the resilience of these systems against adversarial attacks.
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