Evaluate the impact of privacy issues, cyberattacks, and malware on your AI application : Testing Practical Defence from

The video discusses methods to strengthen models against adversarial attacks, focusing on region-based classification (cotac) and thermometer encoding. It evaluates model parameters, noting improvements in accuracy and defense effectiveness. A comparative analysis of defenses is previewed for the next video.

What is the significance of adversarial attacks in model training?

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How does the accuracy of the trained model compare to the original model?

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What is thermometer encoding and how does it affect model accuracy?

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What observations were made regarding the model's performance on normal examples?

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What will be compared in the next video according to the text?

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