Advanced Computer Vision MCQs December 22, 2025August 10, 2024 by u930973931_answers 40 min Score: 0 Attempted: 0/40 Subscribe 1. What is âobject detectionâ in computer vision? (A) Determining the color of an object (B) Recognizing text in images (C) Identifying and locating objects within an image (D) Classifying images into categories 2. Which algorithm is commonly used for object detection? (A) K-means clustering (B) YOLO (You Only Look Once) (C) Principal Component Analysis (D) Support Vector Machine 3. What is the primary purpose of a Convolutional Neural Network (CNN) in computer vision? (A) Performing linear regression (B) Performing data clustering (C) Generating random numbers (D) Extracting features from images 4. Which network architecture is known for its use in image classification tasks? (A) Long Short-Term Memory (B) Recurrent Neural Network (C) VGGNet (D) Generative Adversarial Network 5. What does âimage segmentationâ involve in computer vision? (A) Enhancing image quality (B) Detecting edges in an image (C) Recognizing faces in an image (D) Dividing an image into segments to simplify its analysis 6. Which technique is commonly used for semantic segmentation? (A) Random Forest (B) K-means clustering (C) Principal Component Analysis (D) Fully Convolutional Networks (FCNs) 7. What is the main advantage of using a Generative Adversarial Network (GAN) in computer vision? (A) Detecting edges in images (B) Performing image classification (C) Generating realistic images from noise (D) Clustering image data 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 9. Which of the following is a common technique for image enhancement? (A) K-means clustering (B) Histogram Equalization (C) Principal Component Analysis (D) Support Vector Machine 10. What is âfeature extractionâ in computer vision? (A) Clustering similar images (B) The process of identifying and extracting relevant features from an image (C) Detecting edges in images (D) Generating random images 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 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 13. What is âdepth estimationâ in computer vision? (A) Enhancing image quality (B) Identifying objects in an image (C) Determining the distance of objects from the camera (D) Recognizing text in images 14. Which method is commonly used for face recognition? (A) Eigenfaces (B) K-means clustering (C) Principal Component Analysis (D) Support Vector Machine 15. What is âobject trackingâ in computer vision? (A) Identifying objects in a single frame (B) Following the movement of an object across frames in a video (C) Enhancing image quality (D) Segmenting images into regions 16. Which technique is used to reduce the dimensionality of image data? (A) Histogram Equalization (B) K-means clustering (C) Convolutional Neural Networks (D) Principal Component Analysis (PCA) 17. What does âimage denoisingâ refer to? (A) Detecting objects in an image (B) Removing noise and enhancing the quality of an image (C) Clustering similar images (D) Generating random images 18. Which of the following is a key challenge in âvideo analysisâ? (A) Clustering image data (B) Enhancing image quality (C) Performing image segmentation (D) Handling temporal changes and motion in videos 19. What is âimage stitchingâ in computer vision? (A) Recognizing faces in images (B) Detecting edges in images (C) Combining multiple images to create a panoramic image (D) Generating new images 20. Which approach is commonly used for image classification tasks? (A) Principal Component Analysis (B) K-means clustering (C) Support Vector Machines (D) 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 22. What is âsemantic segmentationâ? (A) Recognizing faces in an image (B) Detecting edges in an image (C) Dividing an image into regions with meaningful labels (D) Performing image classification 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 24. Which of the following methods is used for object recognition in images? (A) Histogram Equalization (B) K-means clustering (C) Principal Component Analysis (D) 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 26. Which technique is used for object localization in images? (A) Principal Component Analysis (B) Bounding box regression (C) K-means clustering (D) Histogram Equalization 27. What does âimage super-resolutionâ refer to? (A) Detecting edges in images (B) Enhancing the resolution and quality of an image (C) Clustering similar images (D) Generating random images 28. What is âdepth sensingâ in computer vision? (A) Enhancing image quality (B) Identifying objects in an image (C) Measuring the distance of objects from the camera using depth sensors (D) Recognizing text in images 29. What does âimage retrievalâ involve? (A) Detecting edges in images (B) Enhancing image quality (C) Searching for and retrieving images from a database based on query images (D) Generating new 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 31. What is âspatial transformationâ in computer vision? (A) Enhancing image quality (B) Detecting objects in an image (C) Applying transformations to spatial coordinates in images, such as rotation and scaling (D) Clustering similar images 32. What does âimage enhancementâ aim to achieve? (A) Generating random images (B) Detecting objects in an image (C) Performing image classification (D) Improving the quality and visual appearance of an image 33. Which algorithm is used for âimage segmentationâ using deep learning? (A) K-means clustering (B) U-Net (C) Principal Component Analysis (D) Support Vector Machine 34. What is âobject recognitionâ in computer vision? (A) Generating new images (B) Identifying and classifying objects within an image (C) Detecting edges in images (D) Enhancing image quality 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 36. Which technique is used for âobject segmentationâ? (A) Support Vector Machine (B) K-means clustering (C) Principal Component Analysis (D) Mask R-CNN 37. What is âfeature matchingâ in computer vision? (A) Enhancing image quality (B) Detecting objects in an image (C) Identifying corresponding features between different images (D) Generating random 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 39. What is âimage classificationâ in computer vision? (A) Enhancing image quality (B) Detecting objects in an image (C) Categorizing images into predefined classes or labels (D) Generating random images 40. Which network is used for âsemantic segmentationâ? (A) K-means clustering (B) U-Net (C) Principal Component Analysis (D) Support Vector Machine