NPTEL Deep Learning Assignment 1 Answers 2023

Deep Learning Assignment 1 Answers 2023 :- Hello students in this article we are going to share Answers of NPTEL Deep Learning Assignment 1 Answers 2023. All the Answers are provided below to help the students as a reference, You must submit your assignment with your own knowledge.

Deep Learning Assignment 1 Answers 2023

1. rom a pack of 52 cards, two cards are drawn together at random. What is the probability of both the cards being kings?

a. 1/15
b. 25/57
c. 35/256
d. 1/221

Answer:- D

2. For a two class problem Bayes minimum error classifier follows which of following rule? (The two different classes are wi and w2, and input feature vector is x)

a. Choose wi if P(wı/x)> P{w2/x)
b. Choose w1 if P{w1)>P(w2)
c. Choose w2 if P(wi)<P(w2)
d. Choose w2 if P(wi/x)>P(w2/x)

Answer:- A

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NPTEL Deep Learning Assignment 1 Answers 2023

3. The texture of the region provides measure of which of the following properties?

a. Smoothness alone
b. Coarseness alone
c. Regularity alone
d. Smoothness, coarseness and regularity

Answer:- D

4. Why convolution neural network is taking oft quickly in recent times? (Check the options that are true.)

a. Access to large amount of digitized data
b. Integration of feature extraction within the training process.
c. Availability of more computational power
d. All of the above.

Answer:- D

5.

NPTEL Deep Learning Assignment 1 Answers 2023
Answer:- C

6. Suppose Fourier descriptor of a shape has K coefticient, and we remove last few coetticient and use only first m (m<K) number of coefficient to reconstruct the shape. What will be effect of using truncated Fourier descriptor on the reconstructed shape

a. We will get a smoothed boundary version of the shape.
b. We will get only the fine details of the boundary of the shape.
c. Full shape ill be reconstructed without any loss of information.
d. Low frequency component of the boundary will be removed from contour of the shape.

Answer:- A

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NPTEL Deep Learning Assignment 1 Answers 2023

7. The plot of distance of the different boundary point from the centroid of the shape taken at various direction is known as

a. Signature descriptor
b. Polygonal descriptor
c. Fourier descriptor.
d. Convex Hull

Answer:- A

8. If the larger values of gray cO-occurrence matrix are concentrated around the main diagonal, then which one of the following will be true?

a. The value of element difference moment will be high.
b. The value of inverse element difference moment will be high.
c. The value of entropy will be very low.
d. None of the above.

Answer:- D

9. Which of the following is a Co-occurrence matrix based descriptor

a. Entropy
b. Uniformity
C. Signature
d. Inverse Element difference moment.
e. All of the above.

Answer:- D

10.

NPTEL Deep Learning Assignment 1 Answers 2023
Answer:- B

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NPTEL Deep Learning Assignment 1 Answers 2022

NPTEL Deep Learning Assignment 1 Answers 2022:- In This article, we have provided the answers of Deep Learning Assignment 1. You must submit your assignment to your own knowledge.

Q1. Signature descriptor of an unknown shape is given in the figure, can you identify the unknown shape?

a. circle
b. square
c. straight line
d. cannot be predicted

Answer:- a) Circle

Q2. To measure the Smoothness, coarseness and regularity of a region we use which of the transformation to extract feature?

a. Gabor Transformation
b. Wavelet Transformation
c. Both Gabor, and Wavelet Transformation.
d. None of the Above

Answer:- c) Both Gabor, and Wavelet Transformation

Q3. Suppose Fourier descriptor of a shape has K coefficient, and we remove last few coefficient and use only first m (m<K) number of coefficient to reconstruct the shape. What will be effect of using truncated Fourier descriptor on the reconstructed shape?

a. We will get a smoothed boundary version of the shape.
b. We will get only the fine details of the boundary of the shape.
c. Full shape will be reconstructed without any loss of information.
d. Low frequency component of the boundary will be removed from contour of the shape.

Answer:- a) We will get a smoothed boundary version of the shape.

Q4. While computing polygonal descriptor of an arbitrary shape using splitting technique, which of the following we take as the starting guess?

a. Vertex joining the two closet point above a threshold on the
b. Vertex joining the two farthest point on the boundary.
c. Vertex joining any two arbitrary point on the boundary.
d. None of the above.

Answer:- b) Vertex joining the two farthest point on the boundary.

Q5. Consider two class Bayes’ Minimum Risk Classifier. Probability of classes W1 and W2 are, P(w1)=0.3 and P(w2)=0.7 respectively. P(x) = 0.545, P(x|w1)=0.65, P(x|w2)=0.5 and the loss matrix values are

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Q6. The Fourier transformation of a complex sequence of number s(k) for k = 0, …, N – 1 is given by:

Answer:- Answer: c)

Q7. The gray co-occurrence matrix C of an unknown image is given in below. What is the value of maximum probability descriptor?

122
212
232

a. 3/17
b. 1/12
c. 3/16
d. 5/16

Answer:- a) 3/17

Q8. Which of the following is not a boundary descriptor.

a. Polygonal Representation
b. Fourier descriptor
c. Signature
d. Histogram.

Answer:- d) Histogram

Q9. We use gray co-occurrence matrix to extract which type of information?

a. Boundary
b. Texture
c. MFCC
d. Zero Crossing rate.

Answer:- b) Texture

Q10. If the larger values of gray co-occurrence matrix are concentrated around the main diagonal, then which one of the following will be true?

a. The value of element difference moment will be low.
b. The value of inverse element difference moment will be low.
c. The value of entropy will be very low.
d. None of the above.

Answer:- a) The value of element difference moment will be low.

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