CNN CNN - Convolutional Neural Networks Semantic Segmentation Questions and Answers 2

Question 1

What are dilated (atrous) convolutions and why are they used in semantic segmentation?

Accepted Answer

Convolutions with gaps between kernel elements that expand the receptive field without increasing parameters or losing resolution

Answer

Dilated convolutions insert zeros between kernel weights (dilation rate > 1), allowing the filter to cover a larger area of the input without downsampling, which is critical for maintaining spatial resolution in segmentation.

Question 2

What is the Atrous Spatial Pyramid Pooling (ASPP) module used for in DeepLab?

Accepted Answer

Capturing multi-scale context by applying parallel dilated convolutions with different dilation rates

Answer

ASPP applies several dilated convolutions with different rates in parallel and concatenates the results, allowing the network to capture object context at multiple scales simultaneously.

Question 3

What does the mean Intersection over Union (mIoU) metric measure in semantic segmentation evaluation?

Accepted Answer

The average of per-class IoU scores, where IoU measures overlap between predicted and ground-truth masks

Answer

mIoU computes IoU (intersection divided by union of predicted and ground-truth regions) for each class and averages them, providing a balanced measure across all classes including rare ones.

Question 4

What is Panoptic Segmentation?

Accepted Answer

A unified task that combines semantic segmentation (stuff) and instance segmentation (things) into a single cohesive map

Answer

Panoptic segmentation assigns each pixel both a semantic class label and an instance ID where applicable, unifying the 'stuff' categories of semantic segmentation with the 'things' categories of instance segmentation.

Question 5

What is the Pyramid Scene Parsing Network (PSPNet) and what problem does it address?

Accepted Answer

A segmentation network that uses a Pyramid Pooling Module to capture global and local context at multiple scales

Answer

PSPNet's Pyramid Pooling Module aggregates features at four different scales using adaptive average pooling, enabling the network to incorporate global context which reduces misclassification from local ambiguity.

CNN - Convolutional Neural Networks Practice Test

CNN - Convolutional Neural Networks Practice Test

CNN CNN - Convolutional Neural Networks Semantic Segmentation Questions and Answers 2