Computer Vision

Object Detection

An AI that can find and identify multiple objects in an image, drawing boxes around each person, car, or sign it sees.

Definition

A computer vision task that both locates and classifies multiple objects within an image or video frame, drawing a bounding box around each one and labeling it. It goes further than image classification, which assigns a single label to a whole image, by answering what objects are present and where they are. Common model families include YOLO, Faster R-CNN, and transformer-based detectors that balance speed against accuracy.

Why it matters

Object detection is the perception layer behind autonomous driving, security and surveillance, retail analytics that count and track products, and medical imaging that flags regions of interest. Any system that must react to specific things in a visual scene depends on it.

Related terms in Computer Vision

CNN (Convolutional Neural Network)

An AI architecture designed to look at pictures, scanning them like a grid to find edges, shapes, and objects.

Computer Vision

Teaching computers to "see" and understand images and video just like humans do.

Vision Transformer (ViT)

Applying the Transformer architecture (originally built for text) to images, and discovering it works even better than CNNs.

Image Segmentation

Teaching an AI to color-code every pixel in an image, identifying exactly where each object begins and ends.

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