Question Paper
Class / Subject: Class 9 (CBSE) · Artificial Intelligence
Chapter: Chapter 4 — Chapter 4: Computer Vision Basics
Time Allowed: 32 minutes
Max Marks: 16
1. What does computer vision enable computers to do? [1]
(A) Interpret visual information from images and videos
(B) Only process text
(C) Only process sound
(D) Nothing useful
2. What does computer vision analyse in images? [1]
(A) Pixels, shapes, colours and patterns
(B) Only file size
(C) Only file names
(D) Nothing specific
3. What is an application of computer vision? [1]
(A) Facial recognition
(B) Only text messaging
(C) Only audio calls
(D) Only printing documents
4. What else uses computer vision? [1]
(A) Self-driving cars detecting obstacles
(B) Only simple calculators
(C) Only paper maps
(D) Only manual driving with no technology
5. What is needed to train computer vision systems? [1]
(A) Large datasets of labelled images
(B) No data at all
(C) Only text data
(D) Only audio data
6. How does AI learn to recognise patterns in images? [1]
(A) Through repeated exposure to examples
(B) Instantly, without any training
(C) By guessing randomly
(D) By ignoring all data
7. What is a limitation of computer vision? [1]
(A) Difficulty in poor lighting or unusual angles
(B) It always works perfectly in every situation
(C) It has no limitations
(D) It can't process any images
8. Why must computer vision systems be carefully tested? [1]
(A) To avoid errors in recognition
(B) Testing is unnecessary
(C) To make them slower
(D) To reduce their accuracy
9. What does computer vision enable computers to do? [1]
(A) Interpret visual information from images and videos
(B) Only process text
(C) Only process sound
(D) Nothing useful
10. What does computer vision analyse in images? [1]
(A) Pixels, shapes, colours and patterns
(B) Only file size
(C) Only file names
(D) Nothing specific
11. What is an application of computer vision? [1]
(A) Facial recognition
(B) Only text messaging
(C) Only audio calls
(D) Only printing documents
12. What else uses computer vision? [1]
(A) Self-driving cars detecting obstacles
(B) Only simple calculators
(C) Only paper maps
(D) Only manual driving with no technology
13. What is needed to train computer vision systems? [1]
(A) Large datasets of labelled images
(B) No data at all
(C) Only text data
(D) Only audio data
14. How does AI learn to recognise patterns in images? [1]
(A) Through repeated exposure to examples
(B) Instantly, without any training
(C) By guessing randomly
(D) By ignoring all data
15. What is a limitation of computer vision? [1]
(A) Difficulty in poor lighting or unusual angles
(B) It always works perfectly in every situation
(C) It has no limitations
(D) It can't process any images
16. Why must computer vision systems be carefully tested? [1]
(A) To avoid errors in recognition
(B) Testing is unnecessary
(C) To make them slower
(D) To reduce their accuracy