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Deep Learning
Deep Learning Receptors and Pooling Explained
Understand convolutional neural network receptors and pooling techniques.
Receptive Fields
Receptive fields are defined portions of space or spatial construct containing units that provide input to a set of units within a corresponding layer.
The receptive field is defined by the filter size of a layer within a convolution neural network. The receptive field is also an indication of the extent of the scope of input data a neuron or unit within a layer can be exposed to (see image below).
The local receptive field is a defined segmented area that is occupied by the content of input data that a neuron within a convolutional layer is exposed to during the process of convolution.
The LeNet paper introduced the first use case of the utilization of the convolutional neural network for character recognition. It also introduced the idea and implementation of local receptive fields within CNN.
But the idea of local receptive fields or rather subsequent units only exposed to a segment of input data — local connections, was…
