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HOW TO USE CNN FOR MAKING PREDICTIONS ON NON-IMAGE DATA?
You can use CNN on any data, but it's recommended to use CNN only on data that have spatial features (It might still work on data that doesn't have spatial features, see DuttaA's comment … From ai.stackexchange.com
IN A CNN, DOES EACH NEW FILTER HAVE DIFFERENT WEIGHTS FOR EACH …
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 * … From ai.stackexchange.com
REDUCE RECEPTIVE FIELD SIZE OF CNN WHILE KEEPING ITS CAPACITY?
Feb 4, 2019 One way to keep the capacity while reducing the receptive field size is to add 1x1 conv layers instead of 3x3 (I did so within the DenseBlocks, there the first layer is a 3x3 conv … From ai.stackexchange.com
WHEN TRAINING A CNN, WHAT ARE THE HYPERPARAMETERS TO TUNE FIRST?
I am training a convolutional neural network for object detection. Apart from the learning rate, what are the other hyperparameters that I should tune? And in what order of importance? Besides, I r... From ai.stackexchange.com
EXTRACT FEATURES WITH CNN AND PASS AS SEQUENCE TO RNN
Sep 12, 2020 But if you have separate CNN to extract features, you can extract features for last 5 frames and then pass these features to RNN. And then you do CNN part for 6th frame and … From ai.stackexchange.com
HOW TO HANDLE RECTANGULAR IMAGES IN CONVOLUTIONAL NEURAL …
I think the squared image is more a choice for simplicity. There are two types of convolutional neural networks Traditional CNNs: CNNs that have fully connected layers at the end, and fully … From ai.stackexchange.com
WHAT IS THE FUNDAMENTAL DIFFERENCE BETWEEN CNN AND RNN?
CNN vs RNN A CNN will learn to recognize patterns across space while RNN is useful for solving temporal data problems. CNNs have become the go-to method for solving any image data … From ai.stackexchange.com
The paper you are citing is the paper that introduced the cascaded convolution neural network. In fact, in this paper, the authors say To realize 3DDFA, we propose to combine two … From ai.stackexchange.com
MACHINE LEARNING - WHAT IS A FULLY CONVOLUTION NETWORK? - ARTIFICIAL ...
Jun 12, 2020 Fully convolution networks A fully convolution network (FCN) is a neural network that only performs convolution (and subsampling or upsampling) operations. Equivalently, an … From ai.stackexchange.com
WHAT IS THE DIFFERENCE BETWEEN A CONVOLUTIONAL NEURAL NETWORK …
Mar 8, 2018 A convolutional neural network (CNN) is a neural network where one or more of the layers employs a convolution as the function applied to the output of the previous layer. From ai.stackexchange.com
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