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Deep Learning for Computer Vision · Quiz 1 · Sep 2025

Deep Learning for Computer Vision · Quiz 1 · Sep 2025

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Question 180 MSQ · 1.0 marks

Consider N cities in a Euclidean plane and use the Euclidean Distance as the distance measure. For each city, take that city as the fulcrum (base) city and compute its Savings tour. From the resulting N Savings tours, select the cheapest tour. What can you conclude about the above procedure?
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This procedure can be used to compute the optimal TSP tour.
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This procedure is not suitable for computing the optimal TSP tour.
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This procedure may not always terminate.
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This procedure will always terminate.       **DL(CV)** **Section Id :** 640653106082 **Section Number :** 11 **Section type :** Online **Mandatory or Optional :** Mandatory **Number of Questions :** 32 **Number of Questions to be attempted :** 32 **Section Marks :** 79 **Display Number Panel :** Yes **Section Negative Marks :** 0 **Group All Questions :** No **Enable Mark as Answered Mark for Review and** No **Clear Response :** **Section Maximum Duration :** 0 **Section Minimum Duration :** 0 **Section Time In :** Minutes **Maximum Instruction Time :** 0

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Question 182 MCQ · 2.0 marks

Source diagram or notation
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130.00
6406535117778.
127.50
6406535117779.
125.00
6406535117780.
120.00

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Question 183 MCQ · 2.0 marks

Which of the following statements is **false**?
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Bilateral filtering is a non-linear, edge-preserving local operation.
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Median filtering is a linear filtering operation.
6406535117783.
Histogram matching uses CDFs to map intensities between images.
6406535117784.
Unsharp masking implements a high-boost (high-pass) effect.

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Question 184 MCQ · 2.0 marks

Which of the following statements is **True**?
6406535117785.Source diagram or notation
6406535117786.Source diagram or notation
6406535117787.Source diagram or notation
6406535117788.Source diagram or notation

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Question 185 MCQ · 2.0 marks

Which filter leaves the center pixel unchanged for any image under convolution?
6406535117789.Source diagram or notation
6406535117790.Source diagram or notation
6406535117791.Source diagram or notation
6406535117792.Source diagram or notation

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Question 186 MCQ · 2.0 marks

Source diagram or notation
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0.9829, 4.05, 1, 4.0673, 4.05, 4.05
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0.8808, 3.50, 1, 3.54, 3.50, 3.50
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0.7311, 2.00, 1, 2.13, 2.00, 2.00
6406535117796.
0.5000, 0.00, 0, 0.69, 0.00, 0.00

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Question 187 MCQ · 2.0 marks

Choose the correct sequence for Canny edge detection: 1. Smooth with Gaussian 2. Compute gradient magnitude & direction 3. Non-maximum suppression 4. Double thresholding (strong/weak) 5. Edge tracking by hysteresis
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2 → 1 → 3 → 4 → 5
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1 → 2 → 3 → 4 → 5
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1 → 3 → 2 → 4 → 5
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3 → 1 → 2 → 5 → 4

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Question 188 MCQ · 2.0 marks

Correct order of SIFT stages is:
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Orientation→ Descriptor → Localization → Extrema Detection
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Extrema Detection → Localization→ Orientation→ Descriptor
6406535117803.
Extrema Detection → Descriptor → Localization → Orientation
6406535117804.
None of these

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Question 189 MCQ · 2.0 marks

In double thresholding, Thigh = 120, Tlow = 50. A pixel with gradient magnitude 45 is classified as:
6406535117805.
Strong edge
6406535117806.
Weak edge
6406535117807.
Non-edge
6406535117808.
Ambiguous

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Question 190 MCQ · 2.0 marks

Source diagram or notation
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1→ii, 2→i, 3→iii, 4→iv
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1→i, 2→ii, 3→iii, 4→iv
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1→i, 2→iv, 3→ii, 4→iii
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1→iv, 2→ii, 3→i, 4→iii

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Question 191 MCQ · 2.0 marks

An RGB image goes through Conv layer: 64 kernels of size 7 x 7, stride 2, then MaxPool 3 x 3, stride 2. The receptive field of a pooling-layer neuron is:
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7 x 7
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9 x 9
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11 x 11
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13 x 13

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Question 192 MCQ · 2.0 marks

Which is **True**?
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Nesterov momentum looks ahead and often converges faster than classical momentum.
6406535117818.
A large fixed learning rate always speeds convergence.
6406535117819.
Adam uses only a first-moment estimate of gradients.
6406535117820.
None of these

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Question 193 MCQ · 2.0 marks

Source diagram or notation
6406535117821.
0.066
6406535117822.
0.071
6406535117823.
0.083
6406535117824.
0.059

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Question 194 MCQ · 2.0 marks

Source diagram or notation
6406535117825.
1→iii, 2→i, 3→v, 4→iv
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1→i, 2→iii, 3→v, 4→ii
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1→iii, 2→iv, 3→v, 4→ii
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1→iii, 2→iv, 3→ii, 4→v

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Question 195 MCQ · 2.0 marks

Source diagram or notation
6406535117829.
1→iii, 2→i, 3→ii
6406535117830.
1→ii, 2→iii, 3→i
6406535117831.
1→iii, 2→ii, 3→i
6406535117832.
None of these

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Question 196 MSQ · 3.0 marks

Which statements are **true**? (Select all that apply)
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6406535117834.Source diagram or notation
6406535117835.Source diagram or notation
6406535117836.Source diagram or notation

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Question 197 MSQ · 3.0 marks

Which statements are **true**? (Select all that apply)
6406535117837.Source diagram or notation
6406535117838.Source diagram or notation
6406535117839.Source diagram or notation
6406535117840.Source diagram or notation

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Question 198 MSQ · 3.0 marks

About convolution and Fourier analysis, which are **true**?
6406535117841.Source diagram or notation
6406535117842.Source diagram or notation
6406535117843.Source diagram or notation
6406535117844.Source diagram or notation

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Question 199 MSQ · 3.0 marks

Which of the following 3 x 3 kernels are separable?
6406535117845.Source diagram or notation
6406535117846.Source diagram or notation
6406535117847.Source diagram or notation
6406535117848.Source diagram or notation

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Question 200 MSQ · 3.0 marks

Which statements are **false**?
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Momentum maintains an EMA-like velocity of gradients/updates.
6406535117850.
RMSProp normalizes step sizes by a running RMS of gradients.
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In the Adam optimizer, the hyper-parameters β1 and β2 control the exponential decay rates for the moving averages of the gradient and its squared vale. Adam with reduces to SGD with momentum. β1 = 0 and β2 = 0 reduces to SGD with momentum.
6406535117852.
Cosine-annealed warm restarts can help escape sharp minima.

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Question 201 NAT · 3.0 marks

Source diagram or notation

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Question 202 NAT · 3.0 marks

Source diagram or notation

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Question 203 NAT · 3.0 marks

Source diagram or notation

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Question 204 NAT · 3.0 marks

Source diagram or notation

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Question 205 NAT · 3.0 marks

Two successive convolutions each with: kernel 7 x 7, padding 3, stride 2. Input is 100 x 100. The final feature-map side length F is _________________.

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Question 206 NAT · 3.0 marks

Source diagram or notation

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Question 207 NAT · 3.0 marks

Source diagram or notation
**NOTE:** Enter your answer in three decimal places.

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Question 208 NAT · 3.0 marks

Source diagram or notation

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Question 209 NAT · 3.0 marks

Source diagram or notation

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Question 210 SHORT_TEXT · 1.5 marks

In Canny, increasing the high threshold tends to (a) _______________ false positives and (b) ____________ false negatives. Based on the above data, answer the given subquestions.
Enter the correct answer for Blank (a) ________________ **NOTE:** Enter the exact answer without any extra space in the beginning or at the end.

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Question 211 SHORT_TEXT · 1.5 marks

In Canny, increasing the high threshold tends to (a) _______________ false positives and (b) ____________ false negatives. Based on the above data, answer the given subquestions.
Enter the correct answer for Blank (b) ________________ **NOTE:** Enter the exact answer without any extra space in the beginning or at the end.

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Question 212 SHORT_TEXT · 1.5 marks

During non-maximum suppression, comparisons are made along the gradient (a) _____________ to keep only local (b) _______________. Based on the above data, answer the given subquestions.
Enter the correct answer for Blank (a) ________________ **NOTE:** Enter the exact answer without any extra space in the beginning or at the end.

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Question 213 SHORT_TEXT · 1.5 marks

During non-maximum suppression, comparisons are made along the gradient (a) _____________ to keep only local (b) _______________. Based on the above data, answer the given subquestions.
Enter the correct answer for Blank (b) ________________ **NOTE:** Enter the exact answer without any extra space in the beginning or at the end.

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Question 214 SHORT_TEXT · 1.5 marks

The gradient of an image I points in the direction of the most rapid change in intensity. Taking image derivatives accentuates (a) ______________ frequencies and hence amplifies noise, since the proportion of noise to signal is larger at (b) _______________ frequencies. The common solution is to smooth the image prior to computing gradients. Based on the above data, answer the given subquestions.
Enter the correct answer for Blank (a) ________________ **NOTE:** Enter the exact answer without any extra space in the beginning or at the end.

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Question 215 SHORT_TEXT · 1.5 marks

The gradient of an image I points in the direction of the most rapid change in intensity. Taking image derivatives accentuates (a) ______________ frequencies and hence amplifies noise, since the proportion of noise to signal is larger at (b) _______________ frequencies. The common solution is to smooth the image prior to computing gradients. Based on the above data, answer the given subquestions.
Enter the correct answer for Blank (b) ________________ **NOTE:** Enter the exact answer without any extra space in the beginning or at the end.

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