Practice Limitations - 22.7 | 22. Convolution Operator | CBSE Class 10th AI (Artificial Intelleigence)
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22.7 - Limitations

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is one limitation of the convolution operator related to computational resources?

💡 Hint: Think about how demanding processing large data can be.

Question 2

Easy

Does convolution handle sequential data well?

💡 Hint: Recall the different types of data that convolution works best with.

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 a major limitation of using convolutional operators with large images?

  • They are inefficient for small images
  • They require significant computational power
  • They always produce high accuracy

💡 Hint: Consider the volume of data being processed.

Question 2

True or False: Convolutional operators are ideal for processing sequential data such as text and audio.

  • True
  • False

💡 Hint: Think about the types of data convolution typically works with.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You are tasked with implementing a CNN for a task requiring processing of 5,000 x 5,000 pixel images. What considerations should you make in terms of computational resources and potential solutions?

💡 Hint: Think about methods to address heavy workloads in your daily tasks.

Question 2

After training a model with a small dataset, you notice it performs poorly on unseen data. What does this imply, and what steps could you take to improve the model's performance?

💡 Hint: Consider how different tests require different amounts of study material to perform well.

Challenge and get performance evaluation