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

Boundary U-Net (correct)

DeepLab

PSPNet

2 / 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

3 / 40

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

Object occlusion

Illumination variation (correct)

Image noise

4 / 40

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

Efficient Neural Network (correct)

Expanded Network

Enhanced Network

5 / 40

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

Mean Squared Error

Cross-Entropy Loss

Dice Loss (correct)

6 / 40

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

Enhancing model performance

Feature extraction refinement

Smoothing segment boundaries (correct)

7 / 40

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

U-Net

FCN

Mask R-CNN (correct)

8 / 40

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

Accelerating training time

Enhancing image resolution

Enlarging the receptive field without increasing parameters (correct)

9 / 40

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

Estimating scene depth

Identifying and tracking individual objects (correct)

Enhancing road visibility

10 / 40

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

U-Net

SegNet

DeepLab (correct)

11 / 40

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

Feature extraction

Boundary refinement (correct)

Pixel classification

12 / 40

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

Lower memory usage

Faster inference time

Improved boundary delineation (correct)

13 / 40

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

FCN (Fully Convolutional Network) (correct)

DeepLab

U-Net

14 / 40

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

PyTorch

Keras

TensorFlow (correct)

15 / 40

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

Depthwise Separable Convolution (correct)

Residual Connection

Atrous Convolution

16 / 40

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

Capturing global context information (correct)

Improving feature extraction

Enhancing image resolution

17 / 40

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

Feature extraction

Pixel classification

Boundary refinement (correct)

18 / 40

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

U-Net

Atrous Convolution

Conditional Random Fields (CRF) (correct)

19 / 40

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

Atrous Convolution (correct)

Depthwise Separable Convolution

Inception Module

20 / 40

What is the purpose of semantic segmentation in computer vision?

Detecting objects

Classifying each pixel into a category (correct)

Enhancing image contrast

21 / 40

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

YOLO

Mask R-CNN

DeepLab (correct)

22 / 40

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

Fast Convolutional Network

Fully Convolutional Network (correct)

Fully Connected Network

23 / 40

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

Precision

Dice Coefficient (correct)

Recall

24 / 40

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

Cross-Reference Framework

Conditional Random Field (correct)

Convolutional Response Filter

25 / 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)

26 / 40

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

SegNet

Mask R-CNN

DeepLab (correct)

27 / 40

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

FCN

DeepLab

U-Net (correct)

28 / 40

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

Dilated Convolution

Residual Connection

Depthwise Separable Convolution (correct)

29 / 40

What is image segmentation in computer vision?

Dividing an image into meaningful segments (correct)

Extracting feature descriptors

Enhancing image resolution

30 / 40

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

DeepLab (correct)

SegNet

U-Net

31 / 40

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

Retaining spatial information (correct)

Faster computation

Higher memory efficiency

32 / 40

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

Handling small datasets effectively (correct)

Low memory usage

High computational cost

33 / 40

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

Dice Coefficient

Mean Average Precision

Intersection over Union (correct)

34 / 40

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

Generative Adversarial Network (correct)

Global Adjustment Network

Gradient Adjustment Network

35 / 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

36 / 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

37 / 40

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

Pyramid Scene Parsing Network (correct)

Pixel Segmentation Network

Patch Selection Perception Network

38 / 40

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

Intersection over Union (IoU) (correct)

F1 score

Mean Absolute Error

39 / 40

Which algorithm combines object detection and image segmentation?

YOLO

SSD

Mask R-CNN (correct)

40 / 40

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

DeepLab (correct)

U-Net

FCN

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Computer MCQs 360April 5, 2024

0 86 1 minute read