Internet of Things
TinkerforgeCode in ActionAbout Me
  • Course Outline
  • 1 - Getting Started
    • Overview
    • Connect to the LED
    • Getting Started
      • Glitch
      • The Application Template
    • Concepts in Programming
      • What is Programming?
      • Variables
      • Functions and Commands
      • Control Structures
      • Loops
      • Objects and Libraries
    • Programming Simple Web Apps
    • Exercises
      • 1.1 Buttons and Inputs
  • 2 - Internet of Things
    • Overview
    • IoT in our Apps
      • Getting Started
        • Hardware Kit
        • Brick Viewer and Daemon
      • Connect to the Devices
        • The Tinkerforge Device Manager
      • Program the Devices
        • RGB LED
        • RGB LED Button
        • OLED Display
        • Sensors
          • Humidity Sensor
          • Ambient Light Sensor
    • Components and Use Cases
    • Exercises
      • 2.1 Lights and Buttons
      • 2.2 Sensors
      • 2.3 Display
  • 3 - Artificial Intelligence
    • Overview
    • AI in our Apps
      • Google's Teachable Machine
      • Face Recognition
      • Training a Custom Model
    • Rules vs. Learning
    • Learning from Data
    • Use Cases
      • Computer Vision
        • Image Classification
        • Handwriting Recognition
    • Machine Learning Algorithms
      • Artificial Neural Networks
      • Decision Trees
      • Logistic Regression
    • Exercises
      • 3.1 Rules vs. Learning
      • 3.2 Fruits and Vegetables
      • 3.3 Face Recognition
      • 3.4 A Classifier for Iris
  • 4 - Cloud & APIs
    • Overview
    • APIs in our Apps
    • Cloud and APIs
      • Weather API
      • NASA Open APIs
      • EDAMAM Nutrition and Recipes API
    • Push Notifications
    • Exercises
  • 5 - App Project
    • Overview
    • Summer 2021
    • Summer 2022
  • Appendix
    • Other Devices
      • Motorized Linear Poti
      • Sound Pressure Sensor
      • NFC Reader
      • Motion Detector
    • UI Features
      • Realtime Charts
      • Countdown Timer
    • Digital Computers
      • Overview
      • The Binary System
      • Code Systems
      • Logic Gates
      • Binary Addition
      • From Analog to Digital
    • Cheat Sheets
    • Projects
      • IoT @ Pickup-Boxes
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  • Slides
  • Video

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  1. 3 - Artificial Intelligence
  2. Use Cases
  3. Computer Vision

Handwriting Recognition

Handwriting recognition is a special case of image classification. It is often used as an introductory example to learn about how a computer can learn to "see" and recognize concepts in images.

PreviousImage ClassificationNextMachine Learning Algorithms

Last updated 4 years ago

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A common task for AI is handwriting recognition. This is a special task in the broader field of computer vision. Using this example, we try to understand how a computer can learn to "see".

Key Takeaways

  • Computers using machine learning algorithms have surpassed human performance in image classification and are now widely used for many tasks.

  • To a computer, an image is a large list of numbers. The task is to learn the patterns that relate to concepts we want to recognize in an image.

  • To teach a computer to recognize handwritten digits, we need many examples (training data) with the correct answers (label).

Slides

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Video

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