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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 25

Question 25

+3 marksOne or more correct options

Select all correct statements .

Select all that apply.

  1. A

    Recurrent models can process ordered sequences of visual features.

  2. B

    Backpropagation through a recurrent model propagates gradient information across unrolled timesteps.

  3. C

    LSTMs and GRUs use gating mechanisms.

  4. D

    Randomly permuting all video frames leaves every temporal model output unchanged by definition.

Show answer

Correct answers

  • A

    Recurrent models can process ordered sequences of visual features.

  • B

    Backpropagation through a recurrent model propagates gradient information across unrolled timesteps.

  • C

    LSTMs and GRUs use gating mechanisms.

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Question 25 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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