Computer Vision Class 10 MCQ

Computer Vision Class 10 MCQ – The CBSE has changed the syllabus of Std. X. The MCQs are made based on the new syllabus and based on the New CBSE textbook, Sample paper and Board Paper.  All the important Information are taken from the Artificial Intelligence Class X Textbook Based on CBSE Board Pattern.

Computer Vision Class 10 MCQ

1. What is the primary objective of the Convolution Layer in a Convolutional Neural Network (CNN)?
a. To flatten the input image
b. To assign importance to various aspects/objects in the image
c. To reduce the spatial size of the input image
d. To perform element-wise multiplication of image arrays

Show Answer ⟶
b. To assign importance to various aspects/objects in the image

2. Which of the following tasks is an example of computer vision?
a. Rescaling an image
b. Correcting brightness levels in an image
c. Object detection in images or videos
d. Changing tones of an image

Show Answer ⟶
c. Object detection in images or videos

3. How is resolution typically expressed?
a. By the number of pixels along the width and height, such as 1280×1024
b. By the brightness level of each pixel, ranging from 0 to 255
c. By the total number of pixels, such as 5 megapixels
d. By the arrangement of pixels in a 2-dimensional grid

Show Answer ⟶
a. By the number of pixels along the width and height, such as 1280×1024

4. What is the core task of image classification?
a. Identifying objects and their locations in images
b. Segmenting objects into individual pixels
c. Assigning an input image one label from a fixed set of categories
d. Detecting instances of real-world objects in images

Show Answer ⟶
c. Assigning an input image one label from a fixed set of categories

5. What is the function of the Rectified Linear Unit (ReLU) layer in a CNN?
a. To reduce the image size for more efficient processing
b. To assign importance to various aspects/objects in the input image
c. To get rid of negative numbers in the feature map and retain positive numbers
d. To perform the convolution operation on the input image

Show Answer ⟶
c. To get rid of negative numbers in the feature map and retain positive numbers

6. Object detection and handwriting recognition are examples of tasks commonly associated with:
a. Computer vision
b. Image processing
c. Both computer vision and image processing
d. Neither computer vision nor image processing

Show Answer ⟶
a. Computer vision

7. What does the pixel value represent in an image?
a. Width of the pixel
b. Brightness or color of the pixel
c. Height of the pixel
d. Resolution of the pixel

Show Answer ⟶
b. Brightness or color of the pixel

8. In the byte image format, what is the range of possible pixel values?
a. 0 to 10
b. 0 to 100
c. 0 to 1000
d. 0 to 255

Show Answer ⟶
d. 0 to 255

9. In a grayscale image, what does the darkest shade represent?
a. Total presence of color
b. Zero value of pixel
c. Lightest shade of gray
d. Maximum pixel value

Show Answer ⟶
b. Zero value of pixel

10. In an RGB image, what does a pixel with an intensity value of 0 represent?
a. Full presence of color
b. No presence of color
c. Maximum brightness level
d. Minimum brightness level

Show Answer ⟶
b. No presence of color

11. Assertion: Object detection is a more complex task than image classification because it involves identifying both the presence and location of objects in an image.
Reasoning: Object detection algorithms need to not only classify the objects present in an image but also accurately localize them by determining their spatial extent.
Select the appropriate option for the statements given above:

a. Both A and R are true and R is the correct explanation of A
b. Both A and R are true and R is not the correct explanation of A
c. A is true but R is false
d. A is False but R is true

Show Answer ⟶
a. Both A and R are true and R is the correct explanation of A

12. Assertion: Grayscale images consist of shades of gray ranging from black to white, where each pixel is represented by a single byte, and the size of the image is determined by its height multiplied by its width.
Reasoning: Grayscale images are represented using a three intensities per pixel, typically ranging from 0 to 255.
Select the appropriate option for the statements given above:

a. Both A and R are true and R is the correct explanation of A
b. Both A and R are true and R is not the correct explanation of A
c. A is true but R is false
d. A is False but R is true

Show Answer ⟶
c. A is true but R is false

13. The _ concept of is used to apply face filters on various social media platforms. (CBSE 2023 – 2024)
a. NLP
b. Computer Vision
c. Data Science
d. Block chain Technology

Show Answer ⟶
b. Computer Vision

14. A leading multinational company operates on a chain of hypermarkets and grocery stores deployed an AI application to make it easier for employees to keep their stores running smoothly. They used thousands of video cameras, weighted sensors on shelves, and other technologies that can tell employees when certain products is starting to go bad. One of the task of the application is to identify bananas that had started to turn brown, eliminating the need for employees to manually inspect fruit. Which of the following domain is used to achieve this?
a. Data sciences
b. Computer vision
c. Natural Language Processing
d. Fuzzy logic

Show Answer ⟶
b. Computer vision

15. An AI system uses two broad classes of data namely content data which includes the raw video streams title, description, etc, and user activity data that includes rating a video, favoriting/liking a video, or subscribing to an uploader, and watch time. Based on this, the AI system measures a user’s engagement and happiness. It then starts computing personalized recommendations to the user. Which of the following applications can you relate to this?
a. self-driving car
b. Siri
c. email filters
d. YouTube

Show Answer ⟶
d. YouTube

16. With reference to AI domain, expand the term CV. (CBSE 2022 – 2023)

Show Answer ⟶
Computer Vision

17. __ is the process of finding instances of real-world objects in images or videos.
a. Instance segmentation
b. Object detection
c. Classification
d. Image segmentation

Show Answer ⟶
b. Object Detection

18. _______is a domain of AI that depicts the capability of a machine to get and analyse visual information and afterwards predict some decisions about it.
a. NLP
b. Data Sciences
c. Augmented Reality
d. Computer Vision

Show Answer ⟶
d. Computer Vision

19. In _, input to machines can be photographs, videos and pictures from thermal or infrared sensors, indicators and different sources.
a. Computer Vision
b. Data Acquisition
c. Data Collection
d. Machine learning

Show Answer ⟶
a. Computer Vision

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