What is a convolutional neural network?
A neural network in which at least one layer is a convolutional layer.
convolutional neural network explained in plain English
A neural network in which at least one layer is a convolutional layer. A typical convolutional neural network consists of some combination of the following layers: - convolutional layers - pooling layers - dense layers Convolutional neural networks have had great success in certain kinds of problems, such as image recognition.
Example
Practitioners refer to convolutional neural network when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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- autoencoder
A system that learns to extract the most important information from the input.
- convolution
In mathematics, casually speaking, a mixture of two functions.
- convolutional filter
One of the two actors in a convolutional operation.
- convolutional layer
A layer of a deep neural network in which a convolutional filter passes along an input matrix.
- convolutional operation
The following two-step mathematical operation: 1.
- depthwise separable convolutional neural network
A convolutional neural network architecture based on Inception, but where Inception modules are replaced with depthwise separable convolutions.
- Neural Network
A layered system that processes information in stages, with each layer detecting slightly more complex patterns than the last.
- pooling
Reducing a matrix (or matrixes) created by an earlier convolutional layer to a smaller matrix.
- stride
In a convolutional operation or pooling, the delta in each dimension of the next series of input slices.
- accelerator chip
A category of specialized hardware components designed to perform key computations needed for deep learning algorithms.