Perception in AI
- (The University of Chicago, Alvin Wei-Cheng Wong)
- Overview
Perception in artificial intelligence (AI) is the process of analyzing and interpreting data from the environment. This includes images, sounds, smells, touch, and other sensory input.
Perception in AI can be used for a variety of purposes, including:
- Understand natural language
- Facial recognition
- Speech recognition
- Object recognition
- Machine hearing
- Music recording and compression
- speech synthesis
Perception helps build machines or robots that react like humans. It's critical for a wide range of applications, from self-driving cars to virtual assistants.
Perception in AI involves breaking down what we see or hear into individual pieces and understanding their meaning. For example, machine perception can tell the location or movement of an object in a scene.
- Vision in AI
Vision in AI, also known as computer vision (CV), is a type of AI that uses machine learning to help computers interpret and analyze visual data.
Computer vision is a type of AI that enables computers to interpret and analyze the visual world, simulating the way humans see and understand their environment. It applies machine learning models to identify and classify objects in digital images and videos, then lets computers react to what they see.
CV's goal is to enable computers to:
- Process, analyze, and interpret visual data
- Identify and classify objects in digital images and videos
- Take actions or make recommendations based on that information
- Correctly identify an object or person in a digital image
- React to what they see
CV enables digital devices, like face detectors and QR code scanners, to identify and process objects in images and videos, just like humans do.
