Podcast
Questions and Answers
How do dense neural networks connect input pixels to neurons in the hidden layer?
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?
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?
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?
How does sliding a patch window across the input image help in neural networks?
What does connecting just a single patch of input to a neuron in the hidden layer achieve?
What does connecting just a single patch of input to a neuron in the hidden layer achieve?
Why is spatial structure considered important in image data for neural networks?
Why is spatial structure considered important in image data for neural networks?
What operation is simply called when we have a weighted summation of all pixels in a patch feeding into the hidden layer?
What operation is simply called when we have a weighted summation of all pixels in a patch feeding into the hidden layer?
How do we define the state of the neurons in the next hidden layer in a convolutional neural network?
How do we define the state of the neurons in the next hidden layer in a convolutional neural network?
What technique is used to shift a patch across an image to extract features in a convolutional neural network?
What technique is used to shift a patch across an image to extract features in a convolutional neural network?
In a convolutional neural network, what is the purpose of applying a four by four filter to an input image?
In a convolutional neural network, what is the purpose of applying a four by four filter to an input image?
What role does the hidden layer play in a convolutional neural network?
What role does the hidden layer play in a convolutional neural network?
Why is the technique of shifting a patch across an image important in feature extraction?
Why is the technique of shifting a patch across an image important in feature extraction?
