Comprehensive Explanation of Convolutional Neural Network (CNN) Layers
An in-depth overview of the architecture and functioning of Convolutional Neural Networks (CNNs), covering all layers involved in their design and operation.
The Semicolon
11.4K views • Feb 20, 2021
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#CNN #ConvolutionalNeuralNetwork #MachineLearning #DeepLearning #DataScience
We understand the working and the architecture of a general Convolutional Neural Network or Convnets. These convnets are used in a lot of Image processing and Computer Vision applications.
We look at each layer one by one. The Convolutional Layer, Max Pooling Layer, Normalisation Layer, Fully Connected Layer. And analyse the input and output of each layer.
Then we connect all these layers and look at the bigger picture.
We understand the working and the architecture of a general Convolutional Neural Network or Convnets. These convnets are used in a lot of Image processing and Computer Vision applications.
We look at each layer one by one. The Convolutional Layer, Max Pooling Layer, Normalisation Layer, Fully Connected Layer. And analyse the input and output of each layer.
Then we connect all these layers and look at the bigger picture.
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Video Information
Views
11.4K
Likes
166
Duration
8:50
Published
Feb 20, 2021
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