Computer Vision
A field of AI that trains computers to interpret and understand visual information from the world — images, videos, and real-time camera feeds. It enables machines to 'see' and make decisions based on what they see.
Why It Matters
Computer vision enables quality inspection in manufacturing, medical imaging analysis, autonomous driving, facial recognition, and augmented reality.
Example
Tesla's Autopilot system using cameras to detect lane markings, traffic signs, pedestrians, and other vehicles in real time.
Think of it like...
Like teaching someone who has never seen the world to understand photographs — the system learns what objects look like by studying millions of examples.
Related Terms
Convolutional Neural Network
A type of neural network specifically designed for processing grid-like data such as images. CNNs use convolutional layers that apply filters to detect patterns like edges, textures, and shapes at different scales.
Object Detection
A computer vision task that identifies and locates specific objects within an image or video, providing both the object class and its position (usually as a bounding box).
Image Classification
A computer vision task that assigns a category label to an entire image. The model determines what the main subject of the image is from a predefined set of categories.
Image Segmentation
A computer vision task that assigns a label to every pixel in an image, dividing it into meaningful regions. It identifies not just what objects are present but their exact shapes and boundaries.