Spatial Structure in Neural Networks
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Questions and Answers

How do dense neural networks connect input pixels to neurons in the hidden layer?

  • By connecting only regions of the input image to a single neuron
  • By connecting every input pixel to a single neuron (correct)
  • By connecting patches of the input to a single neuron
  • By connecting every single pixel to every single neuron
  • Why is it not feasible to connect every single pixel in the input to every single neuron in the hidden layer?

  • Because it leads to overfitting
  • Because it lacks spatial structure
  • Due to the lack of computational power
  • Due to the large dataset size (correct)
  • What is one way to maintain spatial structure in neural networks?

  • By connecting patches of the input to a single neuron (correct)
  • By only connecting regions of the output image
  • By connecting all pixels to all neurons
  • By connecting every input pixel to a single neuron
  • How does sliding a patch window across the input image help in neural networks?

    <p>By connecting patches of the input layer to single neurons</p> Signup and view all the answers

    What does connecting just a single patch of input to a neuron in the hidden layer achieve?

    <p>Maintains spatial structure</p> Signup and view all the answers

    Why is spatial structure considered important in image data for neural networks?

    <p>It allows for more reasonable learning processes</p> Signup and view all the answers

    What operation is simply called when we have a weighted summation of all pixels in a patch feeding into the hidden layer?

    <p>Convolution</p> Signup and view all the answers

    How do we define the state of the neurons in the next hidden layer in a convolutional neural network?

    <p>By applying the same filter of patches across the input image</p> Signup and view all the answers

    What technique is used to shift a patch across an image to extract features in a convolutional neural network?

    <p>Convolution</p> Signup and view all the answers

    In a convolutional neural network, what is the purpose of applying a four by four filter to an input image?

    <p>To detect specific visual features in the image</p> Signup and view all the answers

    What role does the hidden layer play in a convolutional neural network?

    <p>Detects specific features based on weighted inputs</p> Signup and view all the answers

    Why is the technique of shifting a patch across an image important in feature extraction?

    <p>To avoid processing redundant pixel information</p> Signup and view all the answers

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