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Semantic Segmentation QUIZ (MCQ QUESTIONS AND ANSWERS)

Total Correct: 0

Time:20:00

Question: 1

What is the primary advantage of using "deep feature fusion" in semantic segmentation?

Question: 2

In semantic segmentation, what is the primary role of "self-attention mechanisms" in deep neural networks?

Question: 3

What is the primary goal of "real-time semantic segmentation" in computer vision applications?

Question: 4

Which semantic segmentation approach is focused on segmenting objects based on their global context and relationships with other objects in the scene?

Question: 5

In semantic segmentation, what is the primary challenge when dealing with class imbalance in the dataset?

Question: 6

What is the primary advantage of using "dilated convolutions" in semantic segmentation networks?

Question: 7

In semantic segmentation, what is the primary goal of "instance-aware segmentation"?

Question: 8

What is the primary purpose of "semantic boundary detection" in semantic segmentation?

Question: 9

Which semantic segmentation evaluation metric considers the weighted average of per-class IoU scores?

Question: 10

What is the primary challenge in semantic segmentation when dealing with objects that have fine-grained details and intricate textures?

Question: 11

In semantic segmentation, what is the primary advantage of using "multi-scale processing" in deep neural networks?

Question: 12

Which semantic segmentation method is based on the idea of iteratively growing regions and merging segments based on region similarity?

Question: 13

What is the primary purpose of "label transfer" techniques in semantic segmentation?

Question: 14

In semantic segmentation, what is the primary role of "panoptic segmentation"?

Question: 15

What is the primary goal of "binary semantic segmentation" in computer vision?

Question: 16

What is the primary goal of semantic segmentation in computer vision?

Question: 17

In semantic segmentation, what is the primary role of "object proposal methods"?

Question: 18

What is the primary purpose of "data augmentation" in semantic segmentation?

Question: 19

Which deep learning architecture, often pre-trained on large datasets, is used for improving the performance of semantic segmentation models?

Question: 20

What is the primary challenge in semantic segmentation when dealing with objects of varying sizes and scales?

Question: 21

Which evaluation metric in semantic segmentation measures the percentage of true positive predictions compared to the total number of true objects in the image?

Question: 22

What is the primary role of "conditional random fields" (CRFs) in semantic segmentation?

Question: 23

Which semantic segmentation method is based on the idea of "region-based segmentation" and combines image segments into regions with similar characteristics?

Question: 24

In semantic segmentation, what does "instance segmentation" refer to?

Question: 25

What is the primary purpose of "image superpixels" in semantic segmentation?

Question: 26

In semantic segmentation, what is the primary role of "class-agnostic segmentation"?

Question: 27

Which evaluation metric is commonly used to assess the performance of semantic segmentation models, measuring the percentage of correctly classified pixels?

Question: 28

What is the primary challenge in semantic segmentation when dealing with objects that occlude one another?

Question: 29

In semantic segmentation, what is the primary purpose of "fully convolutional networks" (FCNs)?

Question: 30

Which deep learning architecture is commonly used for semantic segmentation, especially in tasks like object detection and scene understanding?