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Deep Learning for Computer Vision End Term: 31 August 2025, Set QIA3 (May 2025 term)

Question 1

+2 marksOne correct option

Why does DETR typically exhibit poor performance in detecting small objects compared to larger ones? Choose the best answer in your opinion.

  1. A

    The CNN backbone used in DETR has a fixed receptive field that’s too large for small objects.

  2. B

    The global self-attention mechanism in DETR tends to dilute the signal from small objects across all image locations.

  3. C

    DETR’s loss function actively discards all detections smaller than 50 × 50 pixels.

  4. D

    The object queries in DETR are programmed to ignore any object smaller than 10% of the image size.

  5. E

    DETR’s encoder-decoder architecture was specifically designed to only detect objects larger than a cat.

Question 2

+2 marksOne correct option

Consider the following Pytorch code:
1. x = torch.tensor([[-3.,2.,3.],[4.,-5.,7.],[20.,3.,2.]])
2. print(torch.mean(x,dim=0,keepdim=True))
The output of the code is:

  1. A

    tensor([ 7., 0., 4.])

  2. B

    tensor([[ -7., 10., -4.]])

  3. C

    tensor([[ -7.],[7.],[4.]])

  4. D

    tensor([ -7., 7., 3.])

  5. E

    tensor([[7., 0., 4.]])

  6. F

    tensor([[ 0.],[7.],[4.]])

Question 3

+2 marksOne correct option

Which one of the following statements is false?

  1. A

    Linear contrast stretching is a point operation.

  2. B

    Moving average is an example of a local operation.

  3. C

    Convolution in the spatial domain cannot be obtained through addition in the frequency domain.

  4. D

    All of these.

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More on the Deep Learning for Computer Vision End Term 31 Aug 2025 Set QIA3 paper

The IIT Madras BS Deep Learning for Computer Vision (Deep Learning for Computer Vision) End Term paper sat on 31 Aug 2025, in the May 2025 term, set QIA3: 49 questions for 72 marks in 180 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.

FeatureDeep Learning for Computer Vision End Term 31 Aug 2025 Set QIA3 at a glance
TermMay 2025 term
SubjectDeep Learning for Computer Vision
Course codeBSDA5006
Questions49
Marks72
Duration180 min
MCQ14
MSQ6
Numerical29
Official paperIIT M IMPROVEMENT AN EXAM QIA3 31 Aug 2025
Negative markingNo negative marking.
Updated

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