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Introduction to Convolutional Neural Networks and its Applications

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Convolutional Neural Networks are deep neural networks that are primarily used for computer vision. CNNs are a specific architecture of Neural Networks that are incredibly effective at dealing with image data. If we train the CNN model with a dog’s image, it identifies dog characteristics such as its color, tail, and legs. Using these features, the model can differentiate between a dog and any other animal.Artificial Neural Networks can also be used for image recognition, but there are certain issues using ANN models for image data. If we use ANNs for fully connected networks for image data, we will end up with many parameters. Another problem is, ANNs flatten out data before feeding it into the network.  If we flatten out the data, we lose all the two-dimensional information of the data sets. Lastly, ANNs perform well where images are extremely similar. CNN can alleviate all these issues with its layers.Convolutional LayerA computer reads images as a matrix of (NxNx3), height, width, ...

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