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4. What is convolution used for in image processing?
a. Applying filters and modifying pixel values
b. Deleting images
c. Storing images as text
d. Making images black and white only
5. What is the purpose of the Rectified Linear Unit (ReLU) function in CNN?
a. To convert the input into a grayscale image
b. To remove negative values from the feature map
c. To reduce the image size
d. To apply edge detection
6. What does the Fully Connected Layer do in a CNN?
a. It applies convolution operations
b. It reduces the image size
c. It classifies the image into specific labels
d. It pools the features from the image
SECTION B (Subjective Type Questions)
Short answer type questions.
1. Why is data preparation important when using No-Code AI tools?
2. What is Teachable Machine, and who developed it?
3. What is the main purpose of Orange Data Mining?
4. What is an image feature in Computer Vision?
5. What is the difference between Max Pooling and Average Pooling in a CNN?
Lab
1. Discuss the challenges of using Computer Vision in society.
2. You are the discipline in-charge of the school. During the festival season, there was a cracker burst in the
boy’s washroom. Discuss the steps taken to identify the student who was responsible for the same. Also
mention how Computer Vision helped.
3. Give the list of software/ applications that use CV. You can take the help from your teacher or from
internet.
4. Create your own convolutions visit the below link and experience the matrix work:
http://setosa.io/ev/image-kernels/
Image Kernel which is a small matrix that lets you apply effects like blurring, sharpening, outlining or
embossing to the image. It also allows you to customise the matrix. The process is “Convolution”, which
primarily uses Machine Learning for 'feature extraction', which is a technique for determining the most
important portions of an image.
Computer Vision 231

