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Deep Learning for Computer Vision · End Term · 13 Sept 2026 · May 2026 term

Deep Learning for Computer Vision End Term 13 Sept 2026 — Question 23

Question 23

+3 marksOne or more correct options

Select all correct statements.

Select all that apply.

  1. A

    Weight sharing allows the same convolution kernel parameters to be used at multiple spatial locations.

  2. B

    Inception-style designs can use multiple processing branches.

  3. C

    Residual connections create shortcut paths across learned transformations.

  4. D

    Finetuning requires discarding all pretrained weights before optimization starts.

Show answer

Correct answers

  • A

    Weight sharing allows the same convolution kernel parameters to be used at multiple spatial locations.

  • B

    Inception-style designs can use multiple processing branches.

  • C

    Residual connections create shortcut paths across learned transformations.

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Question 23 of 37 in the IIT Madras BS Deep Learning for Computer Vision (Deep Learning for Computer Vision) End Term paper sat on 13 Sept 2026, in the May 2026 term (Deep Learning For Computer Vision 13 Sep 26). It carries 3 marks.

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