da5006_2026T2_Q1_NA.pdf
Deep Learning for Computer Vision · Quiz 1 · May 2026
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Question 2 MCQ · 1.0 marks
In the Canny edge detector, which is the correct order of major steps?
Non-maximum suppression → Gaussian smoothing → gradient computation
→ hysteresis thresholding
Gaussian smoothing → gradient computation → non-maximum suppression
→ hysteresis thresholding
Gradient computation → Gaussian smoothing → hysteresis thresholding →
non-maximum suppression
Gaussian smoothing → hysteresis thresholding → non-maximum suppression
→ gradient computation
A published solution is not available for this question yet.
Question 3 MCQ · 1.0 marks
Which is True?
Nesterov momentum looks ahead and often converges faster than classical
momentum.
large fixed learning rate always speeds convergence.
Adam uses only a first-moment estimate of gradients.
None of these.
A published solution is not available for this question yet.
Question 4 MCQ · 1.0 marks
Correct order of SIFT stages is:
Orientation → Descriptor → Localization → Extrema Detection
Extrema Detection → Localization → Orientation → Descriptor
Extrema Detection → Descriptor → Localization → Orientation
None of these
A published solution is not available for this question yet.
Question 5 MCQ · 1.0 marks
Which of the following 3 × 3 kernels is separable?
[[IMAGE:8b706bf6dc852ea6_3_2]]

[[IMAGE:8b706bf6dc852ea6_3_3]]

[[IMAGE:8b706bf6dc852ea6_3_4]]

[[IMAGE:8b706bf6dc852ea6_3_5]]

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Question 6 MCQ · 1.0 marks
Consider the following pyTorch code:
[[IMAGE:8b706bf6dc852ea6_3_6]]

tensor([0.09, 0.24, 0.67])
tensor([0.09, 0.24, 0.66])
tensor([0.09, 0.23, 0.68])
tensor([0.10, 0.27, 0.63])
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Question 7 NAT · 1.0 marks
[[IMAGE:8b706bf6dc852ea6_4_7]]

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Question 8 NAT · 1.0 marks
[[IMAGE:8b706bf6dc852ea6_4_8]]

A published solution is not available for this question yet.
Question 9 NAT · 1.0 marks
[[IMAGE:8b706bf6dc852ea6_5_9]]

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Question 10 NAT · 1.0 marks
[[IMAGE:8b706bf6dc852ea6_5_10]]

A published solution is not available for this question yet.
Question 11 NAT · 1.0 marks
The degrees of freedom for affine transformations in 3D is __
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Question 12 NAT · 1.0 marks
[[IMAGE:8b706bf6dc852ea6_6_11]]

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Question 13 NAT · 1.0 marks
[[IMAGE:8b706bf6dc852ea6_6_12]]

A published solution is not available for this question yet.
Question 14 NAT · 1.0 marks
[[IMAGE:8b706bf6dc852ea6_7_13]]

A published solution is not available for this question yet.