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Knowledge
Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What are two limitations of using ANNs directly on high-resolution images?
💡 Hint: Think about the size of the input and the number of connections.
Question 2
Easy
What does a pooling layer do?
💡 Hint: Consider what happens to dimensions after pooling.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is one main benefit of using pooling layers in CNNs?
- Increase the size of the representation
- Reduce computational load
- Enhance overfitting
💡 Hint: Think about how pooling impacts dimensions.
Question 2
True or False: Dropout increases the risk of overfitting.
- True
- False
💡 Hint: Recall the function of Dropout.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a CNN architecture suitable for a medical imaging task using the principles of Transfer Learning. Describe your architecture and justify your choices.
💡 Hint: Consider how medical images might require specific feature extraction.
Question 2
Explain how you would address both computational efficiency and accuracy in a large-scale image classification problem, referencing CNN mechanisms.
💡 Hint: Focus on interaction between model size and performance.
Challenge and get performance evaluation