Rigorous Computer Vision Test - 78+ MCQs: Computer Vision test: Evaluate Your Knowledge with Vision Processing Questions and Answers

1. Which step is essential in the pre-processing of images for deep learning models?

Data augmentation

Image downsampling

Colorizing images

Adding random noise

2. Which method is commonly used for camera calibration in computer vision?

Radial distortion correction

Homography estimation

Bundle adjustment

Gradient descent optimization

3. In computer vision, what does the acronym OCR stand for?

Object Categorization and Recognition

Optical Character Recognition

Object Classification and Retrieval

Output Color Rendering

4. Which algorithm is commonly used for face recognition in computer vision applications?

K-Means clustering

Support Vector Machines

Principal Component Analysis

Decision Trees

5. What is the primary purpose of image segmentation in computer vision?

Object recognition

Color correction

Noise reduction

Feature extraction

6. Which technique is commonly used for image registration in medical imaging?

Image segmentation

Histogram matching

Mutual Information

Bilateral filtering

7. Which method is commonly used for image super-resolution?

Bilinear interpolation

Image cropping

Recursive filtering

Generative Adversarial Networks (GANs)

8. What is the purpose of the activation function in a neural network?

Adjusting learning rate

Defining loss function

Introducing non-linearity

Selecting optimizer

9. Which method is commonly used for image recognition in the presence of occlusions?

Zero-padding

Spatial transformers

Attention-based models

Graph-based methods

10. In the context of neural style transfer, what role does the content loss play?

Preserving content of the input image

Enhancing artistic style

Controlling feature diversity

Minimizing spatial resolution

11. What is the purpose of a filter in the context of image processing?

Convolving input data

Balancing color channels

Adjusting learning rate

Normalizing layer activations

12. Which technique is commonly used for facial landmark detection?

Haar cascades

Convolutional Neural Networks (CNNs)

Optical Flow

Scale-Invariant Feature Transform (SIFT)

13. In the context of object detection, what is the significance of anchor boxes?

Adjusting learning rate

Defining object classes

Scaling and aspect ratio priors

Reducing model overfitting

14. What is the purpose of non-maximum suppression in object detection algorithms?

Increasing false positives

Removing redundant bounding boxes

Introducing noise in predictions

Randomizing object coordinates

15. Which technique is commonly used for image dehazing?

Retinex theory

Dark channel prior

Mean-Shift clustering

Morphological operations

16. Which image representation is commonly used for feature matching in computer vision?

Histogram of Oriented Gradients (HOG)

Local Binary Pattern (LBP)

Discrete Fourier Transform (DFT)

Canny edge detection

17. Which technique is commonly used for image colorization?

Principal component analysis (PCA)

Adversarial training

Conditional generative models

K-means clustering

18. What is the primary goal of feature extraction in computer vision?

Increasing image complexity

Reducing image dimensionality

Introducing image artifacts

Randomizing image pixels

19. What is the primary advantage of using transfer learning in computer vision?

Reduced training time

Increased model complexity

Random initialization of weights

Avoiding data augmentation

20. Which metric is commonly used to evaluate the performance of object detection algorithms?

Mean Absolute Error

Accuracy

Precision-Recall

F1 Score

21. In the context of deep learning, what is the significance of the vanishing gradient problem?

Overfitting during training

Difficulty in weight initialization

Learning rate instability

Difficulty in propagating gradients through deep networks

22. Which method is commonly used for unsupervised learning in computer vision?

Autoencoders

Transfer learning

Random forests

Principal Component Analysis (PCA)

23. What is the primary purpose of the VGG (Visual Geometry Group) network architecture?

Object detection

Image classification

Semantic segmentation

Feature extraction

24. What is the purpose of the Hough Transform in image processing?

Edge detection

Circle detection

Texture mapping

Image smoothing

25. Which algorithm is commonly used for image segmentation?

K-Means clustering

Linear regression

Decision Trees

Support Vector Machines

26. Which type of neural network is commonly used for image generation?

Autoencoder

Recurrent Neural Network

Feedforward Neural Network

Generative Adversarial Network

27. What is the primary purpose of transfer learning in computer vision?

Enhancing model complexity

Fine-tuning pre-trained models

Random initialization of weights

Avoiding data augmentation

28. In the context of image enhancement, what is the purpose of the Laplacian pyramid?

Edge detection

Contrast adjustment

Spatial filtering

Color space transformation

29. What is the purpose of max pooling in convolutional neural networks?

Reducing spatial dimensions

Increasing model complexity

Introducing skip connections

Balancing training data

30. What is the primary goal of the COCO (Common Objects in Context) dataset?

Image classification

Object detection and segmentation

Facial recognition

Natural language processing

Computer Vision MCQ Test 3