Internet of Things for Architects

Hidden layers and formal description on forwarding propagation

The second convolutional layers use the results of the first layer as input. Remember, the input to the first layer was the original bitmap. The output of the first layer actually represents the location in the 2D bitmap, where a specific primitive was seen. The features of the second layer are more comprehensive than the first. The second layer would have composite structures such as splines and curves. Here, we will describe the role of the neuron, and the computations necessary to force an output from a neuron.

The role of the neuron is to input the sum of all the weights entering it against the pixel values. In the following graph, we see the neuron accepting inputs from the ...