Quiz Space

Deep Learning Practice · End Term · 31 Aug 2025 · May 2025 term · Set QDB3

Question 5: You are building a classifier for a medical imaging datas…

Question 5

+5 marksOne correct option

You are building a classifier for a medical imaging dataset with 5 categories (e.g., types of skin lesions). You decide to use ResNet-18 pretrained on ImageNet and fine-tune only the final layer.

Below is a partially completed PyTorch code snippet:

python
import torch
import torch.nn as nn
from torchvision.models import resnet18


class MedicalImageClassifier(nn.Module):
    def __init__(self):
        super(MedicalImageClassifier, self).__init__()
        self.base = resnet18(pretrained=True)
        # [Missing Line]


    def forward(self, x):
        return self.base(x)


model = MedicalImageClassifier()

Which of the following lines correctly fills in the missing line to adapt the ResNet-18 model for 5-class classification?

  1. A
  2. B
  3. C
  4. D
Show answer

Correct answer

  • A
See the whole paperTake it as a mock test

Question 5 of 22 in the IIT Madras BS Deep Learning Practice (Deep Learning Practice) End Term paper sat on 31 Aug 2025, in the May 2025 term (IIT M DEGREE AN EXAM QDB3 31 Aug 2025). It carries 5 marks.

More questions from this paper

  1. Q1Consider the task of applying a convolutional layer with a stride of 1 to an image of size 111 × 111 (Grayscale), while…
  2. Q2Figure question
  3. Q3Figure question
  4. Q4Consider the following PyTorch CNN model used for a classification task on a small dataset of 32 x 32 RGB images: You r…
  5. Q6The diagram below represents the block-wise flow of the Faster R-CNN object detection pipeline: \boxed{A} \longrightarr…
  6. Q7In the original U-Net architecture, which of the following statements about the decoder (expanding) path is correct?
  7. Q8Which of the following are valid reasons why Convolutional Neural Networks (CNNs) are preferred over fully connected Mu…
  8. Q9In the Faster R-CNN architecture, the Region of Interest (RoI) Pooling layer plays a key role in the object detection p…
  9. Q10Which of the following are valid advantages of YOLO compared to Fast R-CNN or Faster R-CNN?
  10. Q11Which of the following are NOT advantages of AlexNet over InceptionNet?
  11. Q12Which of the following code snippets can be used for data augmentation during training in PyTorch?
  12. Q13Which of the following statements are correct regarding the training dynamics and properties of Generative Adversarial …
  13. Q14SRGAN and ESRGAN are both deep learning architectures designed for single image super- resolution. Which of the followi…
  14. Q15The Multi-stage Progressive Image Restoration Network (MPRNet) is designed to progressively restore degraded images acr…
  15. Q16You are given a feature map of size 64 \times 64 \times 64 (height \times width \times channels). Three convolution ope…
  16. Q17Figure question
  17. Q18You are evaluating an object detection model using the Mean Intersection over Union (mIoU) metric. The model predicts t…
  18. Q19Figure question
  19. Q20Two models, Model 1 and Model 2, are used to reconstruct grayscale images with pixel intensity values in the range [0, …
  20. Q21Two models, Model 1 and Model 2, are used to reconstruct grayscale images with pixel intensity values in the range [0, …
  21. Q22Two models, Model 1 and Model 2, are used to reconstruct grayscale images with pixel intensity values in the range [0, …