Computer Vision Flashcards
What is computer vision?
A field of artificial intelligence that enables computers to interpret and understand visual information from the world, such as images and videos.
How do computers see images?
Images are represented as a grid of pixels, with each pixel having a numerical value corresponding to its color or intensity.
What is a grayscale image?
An image where each pixel has a single value representing its light or dark intensity, typically ranging from 0 (black) to 255 (white).
What is pixel analysis in computer vision?
The process of breaking down an image into tiny dots called pixels, each with a specific color and brightness value.
What is feature extraction?
The analysis of an image to identify patterns, shapes, edges, and other features.
What is the purpose of pattern recognition in computer vision?
To compare identified features to known patterns or objects that the computer has been trained to recognize.
What role does machine learning play in computer vision?
It uses statistical and computational methods to train models on large image datasets, allowing computers to understand visual data by learning from patterns.
What is a Convolutional Neural Network (CNN)?
A type of artificial neural network designed to process and recognize patterns in images through multiple layers.
What is the significance of the year 1957 in computer vision?
The first known digital image scanner, the ‘Cyclograph,’ was developed, transforming images into grids of numbers.
Who are David Hubel and Torsten Wiesel?
Researchers whose experiments on the visual cortex of cats revealed how the brain processes visual information.
What is Optical Character Recognition (OCR)?
A technology that solves the problem of recognizing text printed in any font or typeface.
What is image classification?
The ability to classify an image into a specific category, such as identifying a dog or a person’s face.
What is object detection?
The process of identifying and locating objects within an image or video.
What does image segmentation involve?
Dividing an image into distinct segments, each representing a specific object or region.
What is semantic segmentation?
Classifying each pixel in an image into a specific class or category without distinguishing between different instances.
What is instance segmentation?
Identifying and distinguishing individual objects within an image, providing precise masks for each object.
What is panoptic segmentation?
A hybrid method that combines both semantic and instance segmentation.
What is keypoint detection?
Identifying specific, important points in an image to understand shapes, poses, or movements.
What is image captioning?
Combining computer vision and natural language processing to generate descriptive text for an image.
What are some applications of computer vision?
- Self-driving cars
- Medical imaging
- Google Translate
- Optical Character Recognition
- Facial Recognition
- Machine inspection / Surveillance
- Fingerprint recognition and biometrics
- QR Code Scanning
- 3D model building
What is a major challenge in computer vision related to data?
Training deep learning models requires large amounts of labeled data, which can be time-consuming and expensive to collect.
What is domain adaptation in computer vision?
Techniques to improve model performance on data from a different domain, such as different lighting or camera angles.
What programming language is often recommended for computer vision projects?
Python, due to its ease of use, versatility, and extensive libraries for computer vision applications.
What is the ImageNet dataset?
A large-scale dataset with millions of labeled images across thousands of categories used for object recognition.
