Computer Vision Interview questions
1. What is computer vision?
Computer vision is a field of artificial intelligence that involves the development of algorithms and systems that can analyze, interpret, and understand visual data from the world around us.
2. What are the main applications of computer vision?
Computer vision has a wide range of applications, including image and video analysis, object recognition and classification, robot navigation, and medical image analysis.
3. What are the main challenges of computer vision?
The main challenges of computer vision include dealing with variations in lighting and appearance, handling noise and occlusions, and accurately recognizing and classifying objects in complex environments.
4. How does computer vision differ from image processing?
Computer vision involves the development of algorithms and systems that can analyze, interpret, and understand visual data, while image processing involves the manipulation of images for a specific purpose, such as improving the appearance or extracting information from the image.
5. What is feature extraction in computer vision?
Feature extraction is the process of identifying and extracting relevant features from an image or video that can be used for further analysis or classification. These features may include edges, corners, lines, textures, or other characteristics of the image.
6. What is feature selection in computer vision?
Feature selection is the process of selecting a subset of features from a larger set that are most relevant for a specific task or application. This can help to reduce the dimensionality of the data and improve the efficiency and accuracy of the algorithm.
7. What is a convolutional neural network (CNN)?
A convolutional neural network (CNN) is a type of artificial neural network that is particularly well-suited for processing visual data. It is composed of multiple layers of interconnected neurons that process the input image in a hierarchical manner, extracting features at each layer and ultimately producing a prediction or classification of the image.
8. What is object detection in computer vision?
Object detection is the process of identifying and locating objects in an image or video. This can be done using techniques such as sliding window search, region proposal methods, or deep learning-based approaches.
9. What is object recognition in computer vision?
Object recognition is the process of identifying the class or category to which an object belongs. This can be done using techniques such as feature extraction and classification, or deep learning-based approaches.
10. What is deep learning in computer vision?
Deep learning is a type of machine learning that involves the use of deep neural networks to learn and make predictions or classifications based on large amounts of data. It has been widely used in computer vision for tasks such as object recognition and detection, image classification, and image generation.
11. What is image segmentation in computer vision?
Image segmentation is the process of partitioning an image into distinct regions or segments that correspond to different objects or features in the image. This can be done using techniques such as thresholding, clustering, or deep learning-based approaches.
12. What is image registration in computer vision?
Image registration is the process of aligning or registering two or more images so that they can be compared or combined. This can be useful for tasks such as image fusion, medical image analysis, or object tracking.
13. What is image enhancement in computer vision?
Image enhancement is the process of improving the visual quality or appearance of an image, such as by increasing contrast or removing noise.
14. What is image compression in computer vision?
Image compression is the process of reducing the size of an image by removing redundant or unnecessary information. This can be useful for tasks such as reducing storage requirements or improving the transmission speed of images.
15. What is image recognition in computer vision?
Image recognition is the process of identifying and classifying objects or features in an image. This can be done using techniques such as feature extraction and classification, or deep learning-based approaches.
16. What is image classification in computer vision?
Image classification is the process of assigning a label or category to an image based on its content. This can be done using techniques such as feature extraction and classification, or deep learning-based approaches.
17. What is image segmentation and how is it used in computer vision?
Image segmentation is the process of partitioning an image into distinct regions or segments that correspond to different objects or features in the image. It is used in computer vision for tasks such as object recognition, object tracking, and image restoration.
18. What is pattern recognition in computer vision?
Pattern recognition is the process of identifying patterns or regularities in data and using them to make predictions or classifications. It is often used in computer vision for tasks such as object recognition and classification.
19. What is machine learning in computer vision?
Machine learning is a type of artificial intelligence that involves the development of algorithms and systems that can learn from data and improve their performance over time. It is widely used in computer vision for tasks such as image classification, object detection, and image generation.