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Convolutional Neural Network (CNN)
Structured Output from CNN
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Convolutional neural network can be used for obtaining high- dimensional images rather than being used in class prediction for logistic regression or value prediction for regression problem
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Output of the CNN model can be a tensor S(i,j,k) which represent the pixel(j,k) of ith class, such a collaborative effort can be used to precisely form a perfect image as the output.
Strategies to get output dimension same as the input are
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Pooling is completely avoided or can use pooling with unit stride.
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Pixel-wise labelling involves initial guess of image pixels and refining this guess by interacting with neighboring pixels by parameter sharing.
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Structured Output from CNN
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Questions about the ReLU.