Image Segmentation MCQs With Answers

Computer MCQs 360April 5, 2024

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Welcome to the Image Segmentation MCQs with Answers. In this post, we have shared Image Segmentation Online Test for different competitive exams. Find practice Image Segmentation Practice Questions with answers in Computer Tests exams here. Each question offers a chance to enhance your knowledge regarding Image Segmentation.

Image Segmentation Online Quiz

By presenting 3 options to choose from, Image Segmentation Quiz which cover a wide range of topics and levels of difficulty, making them adaptable to various learning objectives and preferences. You will have to read all the given answers of Image Segmentation Questions and Answers and click over the correct answer.

Test Name: Image Segmentation MCQ Quiz Practice
Type: Quiz Test
Total Questions: 40
Total Marks: 40
Time: 40 minutes

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Image Segmentation

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1 / 40

Which algorithm is suitable for pixel-level segmentation with minimal training data?

DeepLab

FCN (Fully Convolutional Network) (correct)

U-Net

2 / 40

Which algorithm is known for its ability to segment images while preserving fine details?

U-Net

FCN

DeepLab (correct)

3 / 40

What does ENet stand for in the context of lightweight image segmentation networks?

Expanded Network

Efficient Neural Network (correct)

Enhanced Network

4 / 40

Which evaluation metric is used for assessing the quality of segmentation masks in biomedical imaging?

Dice Coefficient (correct)

Precision

Recall

5 / 40

Which technique is used for improving segmentation accuracy by refining boundaries?

Boundary refinement (correct)

Pixel classification

Feature extraction

6 / 40

What does IoU measure in the context of image segmentation evaluation?

Mean Average Precision

Intersection over Union (correct)

Dice Coefficient

7 / 40

What is the primary advantage of using CRF in post-processing for image segmentation?

Improving spatial coherence of segmentation (correct)

Reducing computational cost

Enhancing color contrast

8 / 40

What is the primary advantage of using Mask R-CNN over traditional R-CNN for segmentation tasks?

Higher precision

Faster inference time

Ability to generate instance-level masks (correct)

9 / 40

Which technique is used for reducing memory consumption in deep image segmentation networks?

Atrous Convolution

Depthwise Separable Convolution (correct)

Residual Connection

10 / 40

Which technique is used for improving the efficiency of image segmentation networks by reducing redundant computations?

Depthwise Separable Convolution (correct)

Dilated Convolution

Residual Connection

11 / 40

What does FCN stand for in the context of semantic segmentation?

Fast Convolutional Network

Fully Connected Network

Fully Convolutional Network (correct)

12 / 40

Which algorithm is known for its ability to segment objects with irregular shapes?

SegNet

DeepLab (correct)

U-Net

13 / 40

Which deep learning framework is commonly used for image segmentation tasks?

PyTorch

Keras

TensorFlow (correct)

14 / 40

Which algorithm is known for its ability to segment images at multiple scales?

SegNet

DeepLab (correct)

Mask R-CNN

15 / 40

Which evaluation metric is commonly used to measure the accuracy of segmentation algorithms?

Mean Absolute Error

Intersection over Union (IoU) (correct)

F1 score

16 / 40

What is the purpose of skip connections in U-Net architecture?

Facilitating gradient flow and preserving spatial information (correct)

Enhancing feature extraction

Reducing model size

17 / 40

What is the primary use of instance segmentation in autonomous driving applications?

Enhancing road visibility

Identifying and tracking individual objects (correct)

Estimating scene depth

18 / 40

Which technique is used for handling class imbalance in image segmentation datasets?

Dice Loss (correct)

Mean Squared Error

Cross-Entropy Loss

19 / 40

What is the primary advantage of using FCN over traditional CNN architectures for segmentation?

Higher memory efficiency

Retaining spatial information (correct)

Faster computation

20 / 40

What is the purpose of dilated convolutions in image segmentation networks?

Accelerating training time

Enlarging the receptive field without increasing parameters (correct)

Enhancing image resolution

21 / 40

Which technique is used for refining object boundaries in image segmentation networks?

Feature extraction

Pixel classification

Boundary refinement (correct)

22 / 40

What is the purpose of semantic segmentation in computer vision?

Classifying each pixel into a category (correct)

Enhancing image contrast

Detecting objects

23 / 40

Which technique is used for instance segmentation, where objects of the same class are individually segmented?

Mask R-CNN (correct)

U-Net

FCN

24 / 40

What is the primary difference between semantic segmentation and instance segmentation?

Instance segmentation separates individual objects (correct)

Semantic segmentation labels objects

Instance segmentation enhances image quality

25 / 40

What does CRF stand for in the context of post-processing in segmentation networks?

Convolutional Response Filter

Conditional Random Field (correct)

Cross-Reference Framework

26 / 40

What does GAN stand for in the context of image segmentation enhancement?

Global Adjustment Network

Gradient Adjustment Network

Generative Adversarial Network (correct)

27 / 40

What is the purpose of post-processing techniques like Conditional Random Fields (CRF) in image segmentation?

Feature extraction refinement

Smoothing segment boundaries (correct)

Enhancing model performance

28 / 40

What is the primary use of PSPNet in image segmentation tasks?

Enhancing image resolution

Improving feature extraction

Capturing global context information (correct)

29 / 40

Which algorithm is known for its speed and accuracy in real-time video semantic segmentation?

DeepLab (correct)

YOLO

Mask R-CNN

30 / 40

Which algorithm combines object detection and image segmentation?

Mask R-CNN (correct)

YOLO

SSD

31 / 40

Which algorithm is known for its efficiency in medical image segmentation tasks?

FCN

DeepLab

U-Net (correct)

32 / 40

What is image segmentation in computer vision?

Dividing an image into meaningful segments (correct)

Extracting feature descriptors

Enhancing image resolution

33 / 40

What does PSPNet stand for in the context of image segmentation?

Patch Selection Perception Network

Pyramid Scene Parsing Network (correct)

Pixel Segmentation Network

34 / 40

What is the primary advantage of using U-Net architecture for biomedical image segmentation?

Low memory usage

High computational cost

Handling small datasets effectively (correct)

35 / 40

What is the primary challenge of semantic segmentation in natural scenes with varying lighting conditions?

Illumination variation (correct)

Image noise

Object occlusion

36 / 40

What is the primary advantage of using DeepLabV3+ over DeepLabV3 in image segmentation?

Lower memory usage

Improved boundary delineation (correct)

Faster inference time

37 / 40

Which technique is used for improving segmentation performance by capturing long-range dependencies?

Inception Module

Atrous Convolution (correct)

Depthwise Separable Convolution

38 / 40

Which algorithm is used for medical image segmentation with a focus on boundary delineation?

Boundary U-Net (correct)

DeepLab

PSPNet

39 / 40

Which algorithm is suitable for real-time semantic segmentation applications?

SegNet

U-Net

DeepLab (correct)

40 / 40

Which technique is used for refining segmentation masks by considering pixel-wise dependencies?

Conditional Random Fields (CRF) (correct)

U-Net

Atrous Convolution

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Computer MCQs 360April 5, 2024

0 28 1 minute read