My research project aims to dive deep into the world of neural networks in automotive vehicles and self-driving cars, and detail how automotive companies with vision to produce fully self-driving cars in the future are planning to use NNs (neural networks) and machine learning to make this vision possible, and also explain how NNs are currently used in existing vehicles and their different use cases.
Neural Networks Neural Networks, colloquially known as artificial neural networks (ANNs) and also simulated neural networks (SNNs), are a sub-fiend of machine learning which in it self is a sub-field of Artificial Intelligence, they are the brain of AI and are components of deep learning. The name and structure of NNs are similar to the human brain and were inspired by it, they imitate the biological neurons by signaling to each other (IBM, 2020). ANNs consist of an input layer of neurons, one or two hidden layers of neurons and a final layer of output neurons (Wang, 2003). The diagram illustrated exemplifies a simple architecture of a neural network, the lines which connect the neurons are called weights and are associated with a number which represent the strength of connection between neurons. There are many different types of neural networks and each are used for specific motives. Below are some of the most common ones used in the field: The perceptron “the oldest neur
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