Practice Convolutional Neural Networks (cnns) (18.5.4)

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6 sample questions

Question 1.
What does CNN stand for?
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Think about its specialized purpose in visual processing.
Question 2.
Name one real-world application of CNNs.
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Consider something common in our daily technology.
3Question 3.
What is a characteristic feature of CNNs?
- Use of conventional algorithms
- Automatic feature learning
- Low computational power
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Think about how CNNs process images.
4Question 4.
True or False: Pooling layers help maintain the original size of feature maps.
- True
- False
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Consider what happens during down-sampling.
Question 5.
Design a simple CNN architecture for a digit recognition task using the MNIST dataset. Describe the layers you would use and their functions.
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Think about what layers serve what purpose in a CNN!
Question 6.
Analyze the potential impact of dataset biases on the performance of a CNN in facial recognition tasks. What strategies could mitigate these biases?
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Consider how varied training influences model performance.

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