machine learning - What is a fully convolution network? - Artificial ...
Jun 12, 2020 · 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), …
When training a CNN, what are the hyperparameters to tune first?
Firstly when you say an object detection CNN, there are a huge number of model architectures available. Considering that you have narrowed down on your model architecture a CNN will …
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 …
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 * …
My CNN model performs bad on new (self-created) pictures, what …
May 7, 2020 · I once trained a CNN model on poor quality images and with very good validation accuracy but when I tested on image from my camera it didn't work at all. I degraded the …
How to use CNN for making predictions on non-image data?
Feb 7, 2019 · 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 …
What are acting as weights in a convolution neural network?
Jan 19, 2021 · In a CNN, the weights are the kernels/filters of the CNN, i.e. the matrices that you use to perform the convolution (or cross-correlation) operation in a convolutional layer. So, …
How do I handle large images when training a CNN?
Aug 31, 2017 · Commonly researches scale the images to a resonable size. But if that's not an option for you, you'll need to restrict your CNN. In addition to downsampling in early layers, I …
neural networks - Are fully connected layers necessary in a CNN ...
Aug 6, 2019 · A convolutional neural network (CNN) that does not have fully connected layers is called a fully convolutional network (FCN). See this answer for more info. An example of an …
deep learning - Artificial Intelligence Stack Exchange
May 22, 2020 · This is the same thing as in CNNs. The only difference is that, in CNNs, the kernels are the learnable (or trainable) parameters, i.e. they change during training so that the …