1. What is âobject detectionâ in computer vision?
A) Identifying and locating objects within an image
B) Recognizing text in images
C) Determining the color of an object
D) Classifying images into categories
Answer: A) Identifying and locating objects within an image
2. Which algorithm is commonly used for object detection?
A) YOLO (You Only Look Once)
B) K-means clustering
C) Principal Component Analysis
D) Support Vector Machine
Answer: A) YOLO (You Only Look Once)
3. What is the primary purpose of a Convolutional Neural Network (CNN) in computer vision?
A) Extracting features from images
B) Performing data clustering
C) Generating random numbers
D) Performing linear regression
Answer: A) Extracting features from images
4. Which network architecture is known for its use in image classification tasks?
A) VGGNet
B) Recurrent Neural Network
C) Long Short-Term Memory
D) Generative Adversarial Network
Answer: A) VGGNet
5. What does âimage segmentationâ involve in computer vision?
A) Dividing an image into segments to simplify its analysis
B) Detecting edges in an image
C) Recognizing faces in an image
D) Enhancing image quality
Answer: A) Dividing an image into segments to simplify its analysis
6. Which technique is commonly used for semantic segmentation?
A) Fully Convolutional Networks (FCNs)
B) K-means clustering
C) Principal Component Analysis
D) Random Forest
Answer: A) Fully Convolutional Networks (FCNs)
7. What is the main advantage of using a Generative Adversarial Network (GAN) in computer vision?
A) Generating realistic images from noise
B) Performing image classification
C) Detecting edges in images
D) Clustering image data
Answer: A) Generating realistic images from noise
8. What is âimage registrationâ in the context of computer vision?
A) Aligning two or more images to achieve spatial correspondence
B) Classifying images into categories
C) Detecting objects within an image
D) Segmenting images into regions
Answer: A) Aligning two or more images to achieve spatial correspondence
9. Which of the following is a common technique for image enhancement?
A) Histogram Equalization
B) K-means clustering
C) Principal Component Analysis
D) Support Vector Machine
Answer: A) Histogram Equalization
10. What is âfeature extractionâ in computer vision?
A) The process of identifying and extracting relevant features from an image
B) Clustering similar images
C) Detecting edges in images
D) Generating random images
Answer: A) The process of identifying and extracting relevant features from an image
11. What is the primary use of âoptical flowâ in computer vision?
A) Estimating motion between two image frames
B) Classifying images
C) Generating new images
D) Detecting edges in images
Answer: A) Estimating motion between two image frames
12. Which algorithm is used for detecting corners in an image?
A) Harris Corner Detection
B) K-means clustering
C) Principal Component Analysis
D) Support Vector Machine
Answer: A) Harris Corner Detection
13. What is âdepth estimationâ in computer vision?
A) Determining the distance of objects from the camera
B) Identifying objects in an image
C) Enhancing image quality
D) Recognizing text in images
Answer: A) Determining the distance of objects from the camera
14. Which method is commonly used for face recognition?
A) Eigenfaces
B) K-means clustering
C) Principal Component Analysis
D) Support Vector Machine
Answer: A) Eigenfaces
15. What is âobject trackingâ in computer vision?
A) Following the movement of an object across frames in a video
B) Identifying objects in a single frame
C) Enhancing image quality
D) Segmenting images into regions
Answer: A) Following the movement of an object across frames in a video
16. Which technique is used to reduce the dimensionality of image data?
A) Principal Component Analysis (PCA)
B) K-means clustering
C) Convolutional Neural Networks
D) Histogram Equalization
Answer: A) Principal Component Analysis (PCA)
17. What does âimage denoisingâ refer to?
A) Removing noise and enhancing the quality of an image
B) Detecting objects in an image
C) Clustering similar images
D) Generating random images
Answer: A) Removing noise and enhancing the quality of an image
18. Which of the following is a key challenge in âvideo analysisâ?
A) Handling temporal changes and motion in videos
B) Enhancing image quality
C) Performing image segmentation
D) Clustering image data
Answer: A) Handling temporal changes and motion in videos
19. What is âimage stitchingâ in computer vision?
A) Combining multiple images to create a panoramic image
B) Detecting edges in images
C) Recognizing faces in images
D) Generating new images
Answer: A) Combining multiple images to create a panoramic image
20. Which approach is commonly used for image classification tasks?
A) Convolutional Neural Networks (CNNs)
B) K-means clustering
C) Support Vector Machines
D) Principal Component Analysis
Answer: A) Convolutional Neural Networks (CNNs)
21. What does âimage captioningâ involve in computer vision?
A) Generating descriptive text for an image
B) Identifying objects in an image
C) Enhancing image quality
D) Detecting edges in images
Answer: A) Generating descriptive text for an image
22. What is âsemantic segmentationâ?
A) Dividing an image into regions with meaningful labels
B) Detecting edges in an image
C) Recognizing faces in an image
D) Performing image classification
Answer: A) Dividing an image into regions with meaningful labels
23. What does âinstance segmentationâ refer to?
A) Segmenting each object instance in an image individually
B) Identifying objects in an image
C) Enhancing image quality
D) Detecting edges in images
Answer: A) Segmenting each object instance in an image individually
24. Which of the following methods is used for object recognition in images?
A) Region-based Convolutional Neural Networks (R-CNNs)
B) K-means clustering
C) Principal Component Analysis
D) Histogram Equalization
Answer: A) Region-based Convolutional Neural Networks (R-CNNs)
25. What is âaction recognitionâ in video analysis?
A) Identifying and classifying actions or activities occurring in video sequences
B) Enhancing image quality
C) Detecting objects in images
D) Segmenting images into regions
Answer: A) Identifying and classifying actions or activities occurring in video sequences
26. Which technique is used for object localization in images?
A) Bounding box regression
B) Principal Component Analysis
C) K-means clustering
D) Histogram Equalization
Answer: A) Bounding box regression
27. What does âimage super-resolutionâ refer to?
A) Enhancing the resolution and quality of an image
B) Detecting edges in images
C) Clustering similar images
D) Generating random images
Answer: A) Enhancing the resolution and quality of an image
28. What is âdepth sensingâ in computer vision?
A) Measuring the distance of objects from the camera using depth sensors
B) Identifying objects in an image
C) Enhancing image quality
D) Recognizing text in images
Answer: A) Measuring the distance of objects from the camera using depth sensors
29. What does âimage retrievalâ involve?
A) Searching for and retrieving images from a database based on query images
B) Enhancing image quality
C) Detecting edges in images
D) Generating new images
Answer: A) Searching for and retrieving images from a database based on query images
30. Which method is commonly used for âface detectionâ?
A) Haar Cascades
B) K-means clustering
C) Principal Component Analysis
D) Support Vector Machine
Answer: A) Haar Cascades
31. What is âspatial transformationâ in computer vision?
A) Applying transformations to spatial coordinates in images, such as rotation and scaling
B) Detecting objects in an image
C) Enhancing image quality
D) Clustering similar images
Answer: A) Applying transformations to spatial coordinates in images, such as rotation and scaling
32. What does âimage enhancementâ aim to achieve?
A) Improving the quality and visual appearance of an image
B) Detecting objects in an image
C) Performing image classification
D) Generating random images
Answer: A) Improving the quality and visual appearance of an image
33. Which algorithm is used for âimage segmentationâ using deep learning?
A) U-Net
B) K-means clustering
C) Principal Component Analysis
D) Support Vector Machine
Answer: A) U-Net
34. What is âobject recognitionâ in computer vision?
A) Identifying and classifying objects within an image
B) Generating new images
C) Detecting edges in images
D) Enhancing image quality
Answer: A) Identifying and classifying objects within an image
35. What does âaction detectionâ involve in video analysis?
A) Identifying and locating actions occurring in video frames
B) Enhancing image quality
C) Recognizing faces in images
D) Clustering image data
Answer: A) Identifying and locating actions occurring in video frames
36. Which technique is used for âobject segmentationâ?
A) Mask R-CNN
B) K-means clustering
C) Principal Component Analysis
D) Support Vector Machine
Answer: A) Mask R-CNN
37. What is âfeature matchingâ in computer vision?
A) Identifying corresponding features between different images
B) Detecting objects in an image
C) Enhancing image quality
D) Generating random images
Answer: A) Identifying corresponding features between different images
38. What does âscene understandingâ involve in computer vision?
A) Interpreting and understanding the content and context of a scene in an image
B) Detecting edges in images
C) Performing image classification
D) Generating new images
Answer: A) Interpreting and understanding the content and context of a scene in an image
39. What is âimage classificationâ in computer vision?
A) Categorizing images into predefined classes or labels
B) Detecting objects in an image
C) Enhancing image quality
D) Generating random images
Answer: A) Categorizing images into predefined classes or labels
40. Which network is used for âsemantic segmentationâ?
A) U-Net
B) K-means clustering
C) Principal Component Analysis
D) Support Vector Machine
Answer: A) U-Net
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