18. Introduction to Computer Vision - CBSE 10 AI (Artificial Intelleigence)
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18. Introduction to Computer Vision

18. Introduction to Computer Vision

Computer Vision is a crucial subfield of Artificial Intelligence that allows machines to interpret and understand visual information similarly to humans. It encompasses various processes like image classification, object detection, and facial recognition, utilizing tools such as OpenCV and TensorFlow. The real-world applications of computer vision are widespread, spanning healthcare, security, and autonomous vehicles, while also presenting technical challenges and limitations.

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  1. 18
    Introduction To Computer Vision

    Computer Vision is a subfield of AI that enables machines to interpret and...

  2. 18.1
    What Is Computer Vision?

    Computer Vision is a branch of AI that allows computers to interpret and...

  3. 18.2
    How Computer Vision Works

    This section describes the three fundamental steps of computer vision: image...

  4. 18.2.1
    Image Acquisition

    Image acquisition is the first step in the computer vision process,...

  5. 18.2.2
    Processing & Analysis

    This section outlines the processing and analysis involved in computer...

  6. 18.2.3
    Understanding Or Interpretation

    Understanding or interpretation in computer vision refers to how machines...

  7. 18.3
    Key Components Of Computer Vision

    This section presents the key components of computer vision, highlighting...

  8. 18.4
    Tools And Libraries Used In Computer Vision

    This section discusses the essential tools and libraries utilized in...

  9. 18.5
    Techniques Used In Computer Vision

    This section explores key techniques used in computer vision, enhancing...

  10. 18.5.1
    Edge Detection

    Edge detection is a crucial computer vision technique that identifies...

  11. 18.5.2
    Color Detection And Filtering

    Color detection and filtering is a crucial technique in computer vision that...

  12. 18.5.3
    Feature Extraction

    Feature extraction is a crucial technique in computer vision that identifies...

  13. 18.5.4
    Convolutional Neural Networks (Cnns)

    Convolutional Neural Networks (CNNs) are specialized deep learning models...

  14. 18.5.5
    Image Augmentation

    Image augmentation is a technique used in training AI models that generates...

  15. 18.6
    Real-World Applications Of Computer Vision

    Computer vision finds extensive applications across various industries,...

  16. 18.7
    Advantages And Limitations

    This section outlines the advantages and limitations of computer vision,...

  17. 18.8

    Computer Vision enables machines to process and understand visual...

What we have learnt

  • Computer Vision enables machines to see and comprehend the visual world.
  • It automates tasks like object detection and image classification.
  • Tools like OpenCV and TensorFlow are fundamental in implementing computer vision techniques.

Key Concepts

-- Image Acquisition
The process of capturing images or videos using cameras or other devices.
-- Object Detection
The technique used to identify objects within an image and locate them accurately.
-- Convolutional Neural Networks (CNNs)
A deep learning model specifically designed for processing visual data.
-- Facial Recognition
The technology used to identify or verify a person's identity based on their facial features.
-- Image Segmentation
A process that divides an image into segments or regions for better object detection.

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