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3 cards from this section. Quick, good the night before a test.
What is Computer Vision?
Think about how we perceive images.
Name a key architecture used in image classification.
What networks are commonly used for image-related tasks?
What does CNN stand for?
What do we call the neural networks specifically designed for images?
True or False: Data augmentation is used to improve model performance by increasing training dataset diversity.
What technique can we use to 'create' more data?
Design a simple CNN structure for image classification. Discuss potential layers and their configurations.
Think about how you would extract features from an image progressively.
Evaluate the impact of data augmentation on model performance. Provide theoretical scenarios.
What ensures a model learns well and doesn't just memorize?
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