Also known as: CNN
A convolutional neural network, or CNN, is a neural network architecture that uses convolutional layers to learn spatial or local patterns in data. CNNs are especially common in image and video analysis, but they can also be applied to other structured inputs such as audio or sequences.
In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep neural network most commonly applied to image analysis. CNNs use a variation of multilayer perceptrons designed to require minimal preprocessing. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on their shared-weights architecture and translation invariance characteristics.
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.