5. Recognition

Semantic Segmentation — Quiz

Test your understanding of semantic segmentation with 5 practice questions.

Practice Questions

Question 1

Which of the following best describes the primary goal of semantic segmentation?

Question 2

In the context of Fully Convolutional Networks (FCNs) for semantic segmentation, what is the main reason for replacing fully connected layers with convolutional layers?

Question 3

The U-Net architecture is particularly effective for semantic segmentation in medical imaging due to its ability to capture both fine-grained details and global context. Which architectural component primarily facilitates the preservation of fine-grained details?

Question 4

When training a semantic segmentation model, a common challenge is class imbalance, where some classes have significantly fewer pixels than others. Which of the following loss functions is often used to mitigate this issue?

Question 5

Consider a semantic segmentation model where the output prediction map has a lower resolution than the input image. For example, an input image of size $512 \times 512$ pixels results in a prediction map of size $128 \times 128$ pixels. What technique is typically applied to upsample this prediction map to match the original image size for accurate pixel-wise comparison?