Neural Network Training with Convolutional Neural Net (CNN)

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Convolutional Neural Networks (CNNs) are a class of deep neural networks designed for tasks involving grid-structured data, such as images and video. CNNs have proven highly effective in computer vision tasks, achieving state-of-the-art performance in tasks like image classification, object detection, and image segmentation. Here’s an overview of key concepts related to CNNs:

I. Convolutional Neural Network Architect:

Let’s illustrate the architecture of a Convolutional Neural Network (CNN).

      Input Image
           ↓
     ----------------
    |   Conv Layer   |
     ----------------
           ↓
     ----------------
    |   Pooling      |
     ----------------
           ↓
     ________________
    |                |
    |   Conv Layer   |
    |________________|
           ↓
     ----------------
    |   Pooling      |
     ----------------
           ↓
     ----------------
    |   Conv Layer   |
     ----------------
           ↓
     ________________
    |                |
    |   Fully        |
    |   Connected    |
    |   Layer        |
    |________________|
           ↓
     ----------------
    |   Output       |
    |   Layer        |
     ----------------

• The input is an image, typically represented as a grid of pixel…