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

What is the purpose of semantic segmentation in computer vision?

Detecting objects

Classifying each pixel into a category (correct)

Enhancing image contrast

2 / 40

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

Intersection over Union (correct)

Mean Average Precision

Dice Coefficient

3 / 40

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

Generative Adversarial Network (correct)

Gradient Adjustment Network

Global Adjustment Network

4 / 40

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

U-Net

Conditional Random Fields (CRF) (correct)

Atrous Convolution

5 / 40

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

Faster inference time

Higher precision

Ability to generate instance-level masks (correct)

6 / 40

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

Dice Loss (correct)

Mean Squared Error

Cross-Entropy Loss

7 / 40

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

Keras

TensorFlow (correct)

PyTorch

8 / 40

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

Enhancing color contrast

Reducing computational cost

Improving spatial coherence of segmentation (correct)

9 / 40

What is image segmentation in computer vision?

Dividing an image into meaningful segments (correct)

Enhancing image resolution

Extracting feature descriptors

10 / 40

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

Faster computation

Higher memory efficiency

Retaining spatial information (correct)

11 / 40

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

FCN

U-Net

Mask R-CNN (correct)

12 / 40

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

Boundary U-Net (correct)

DeepLab

PSPNet

13 / 40

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

Dilated Convolution

Depthwise Separable Convolution (correct)

Residual Connection

14 / 40

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

Enhancing image resolution

Enlarging the receptive field without increasing parameters (correct)

Accelerating training time

15 / 40

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

Feature extraction

Boundary refinement (correct)

Pixel classification

16 / 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

17 / 40

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

Lower memory usage

Improved boundary delineation (correct)

Faster inference time

18 / 40

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

Fully Connected Network

Fully Convolutional Network (correct)

Fast Convolutional Network

19 / 40

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

Depthwise Separable Convolution

Atrous Convolution (correct)

Inception Module

20 / 40

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

F1 score

Mean Absolute Error

Intersection over Union (IoU) (correct)

21 / 40

Which algorithm combines object detection and image segmentation?

Mask R-CNN (correct)

SSD

YOLO

22 / 40

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

Conditional Random Field (correct)

Convolutional Response Filter

Cross-Reference Framework

23 / 40

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

U-Net

SegNet

DeepLab (correct)

24 / 40

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

Illumination variation (correct)

Image noise

Object occlusion

25 / 40

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

Patch Selection Perception Network

Pyramid Scene Parsing Network (correct)

Pixel Segmentation Network

26 / 40

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

Expanded Network

Enhanced Network

Efficient Neural Network (correct)

27 / 40

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

Enhancing feature extraction

Facilitating gradient flow and preserving spatial information (correct)

Reducing model size

28 / 40

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

Handling small datasets effectively (correct)

High computational cost

Low memory usage

29 / 40

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

Atrous Convolution

Residual Connection

Depthwise Separable Convolution (correct)

30 / 40

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

U-Net (correct)

DeepLab

FCN

31 / 40

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

FCN (Fully Convolutional Network) (correct)

U-Net

DeepLab

32 / 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

33 / 40

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

Pixel classification

Boundary refinement (correct)

Feature extraction

34 / 40

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

Identifying and tracking individual objects (correct)

Estimating scene depth

Enhancing road visibility

35 / 40

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

DeepLab (correct)

Mask R-CNN

YOLO

36 / 40

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

Precision

Dice Coefficient (correct)

Recall

37 / 40

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

Mask R-CNN

SegNet

DeepLab (correct)

38 / 40

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

Capturing global context information (correct)

Improving feature extraction

Enhancing image resolution

39 / 40

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

SegNet

U-Net

DeepLab (correct)

40 / 40

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

U-Net

FCN

DeepLab (correct)

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Computer MCQs 360April 5, 2024

0 25 1 minute read