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Bookmark or Share- machine learning - What is a fully convolution network? - Artificial ...The typical convolution neural network (CNN) is not fully convolutional because it often contains fully connected layers too (which do not perform the convolution operation), which are parameter-rich, in the sense that they have many parameters (compared to their equivalent convolution layers), although the fully connected layers can also be ...
- How can the convolution operation be implemented as a matrix ...To show how the convolution (in the context of CNNs) can be viewed as matrix-vector multiplication, let's suppose that we want to apply a $3 \times 3$ kernel to a $4 \times 4$ input, with no padding and with unit stride.
- In a CNN, does each new filter have different weights for each input ...Typically for a CNN architecture, in a single filter as described by your number_of_filters parameter, there is one 2D kernel per input channel. There are input_channels * number_of_filters sets of weights, each of which describe a convolution kernel. So the diagrams showing one set of weights per input channel for each filter are correct.
- What is a cascaded convolutional neural network?To realize 3DDFA, we propose to combine two achievements in recent years, namely, Cascaded Regression and the Convolutional Neural Network (CNN). This combination requires the introduction of a new input feature which fulfills the "cascade manner" and "convolution manner" simultaneously (see Sec. 3.2) and a new cost function which can model the ...
- What is the computational complexity of the forward pass of a ...Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.
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