Understanding deep learning
Computer vision as a field has a long history. With the emergence of deep learning, computer vision has proven to be useful for various applications. Deep learning is a collection of techniques from artificial neural network (ANN), which is a branch of machine learning. ANNs are modelled on the human brain; there are nodes linked to each other that pass information to each other. In the following sections, we will discuss in detail how deep learning works by understanding the commonly used basic terms.
Perceptron
An artificial neuron or perceptron takes several inputs and performs a weighted summation to produce an output. The weight of the perceptron is determined during the training process and is based on the training data. The following is adiagram of the perceptron:
The inputs are weighted and summed as shown in the preceding image. The sum is then passed through a unit step function, in this case, for a binary classification problem. A perceptron can only learn...
