Quiz Space

Deep Learning Practice · End Term · 13 Sept 2026 · May 2026 term · Set S2

Question 22: In the original U-Net used for dense prediction (and ada…

Question 22

+2 marksNumerical answer

In the original U-Net used for dense prediction (and adaptable to depth estimation), each encoder stage applies two successive 3×3 convolutions with no padding (stride 1), followed by a 2×2 max-pooling with stride 2. If the input feature map to one such encoder stage has spatial size 132 × 132, what is the output height of the feature map after both convolutions and the max-pooling of that stage? The width is the same; enter one integer only.

Show answer

Correct answer: 64

Question 22 of 31 in the IIT Madras BS Deep Learning Practice (Deep Learning Practice) End Term paper sat on 13 Sept 2026, in the May 2026 term (Deep Learning Practice 13 Sep 26 (Session 2)). It carries 2 marks.

More questions from this paper

  1. Q1Based on the above data, answer the given subquestions.
  2. Q2Based on the above data, answer the given subquestions.
  3. Q3Using the actual flattened feature size from previous question number 2, how many learnable parameters (weights + bias)…
  4. Q4Which of the following statements about the (corrected) model are true?
  5. Q5Figure question
  6. Q6Figure question
  7. Q7Which layer is responsible for the decoder failing to reach the target 96×96 output, and why?
  8. Q8Figure question
  9. Q9Figure question
  10. Q10Figure question
  11. Q11What is the parameter compression ratio (standard ÷ depthwise-separable), rounded to 2 decimal places?
  12. Q12Figure question
  13. Q13Which of the following statements correctly identify a real bug in the given code ?
  14. Q14Based on the above data, answer the given subquestions.
  15. Q15Based on the above data, answer the given subquestions.
  16. Q16A convolutional layer receives a feature map with 24 input channels and applies 40 filters, each of spatial size 5 × 5.…
  17. Q17A convolutional layer is applied to a 48 × 48 input using a 5 × 5 filter with zero-padding of 2 and stride 2. Using the…
  18. Q18The final classification head applies a softmax over the pre-activation scores (logits). For a 3-class problem, the log…
  19. Q19Following the VGG design philosophy of replacing a single large-kernel convolution with a cascade of small 3 × 3, strid…
  20. Q20Figure question
  21. Q21The decoder of a depth-estimation network upsamples feature maps using a transposed convolution ("up-convolution") with…
  22. Q23The SRGAN discriminator is a stack of 8 convolutional layers, all using 3 × 3 kernels with padding 1, and strides alter…
  23. Q24Efficient restoration networks (e.g., LaKDNet) replace standard convolutions with depth-wise separable convolutions (a …
  24. Q25Which of the following statements about the ResNet architecture and its standard training recipe are correct?
  25. Q26Which of the following statements about the GoogLeNet / Inception architecture are correct?
  26. Q27Which of the following statements correctly describe the Region Proposal Network (RPN) in Faster R-CNN?
  27. Q28Which of the following statements about evaluating object detectors with mAP are correct?
  28. Q29Which of the following statements correctly describe an encoder–decoder (U-Net style) architecture used for monocular d…
  29. Q30Regarding the channel-attention module in CBAM, which of the following are correct?
  30. Q31In the multi-scale deep network for single-image depth estimation (Eigen et al.), the architecture is split into a coar…