Deep Learning Approaches for IoV Applications and Services

Autor: Rashid A. Saeed, Elmustafa Sayed Ali, Lina Elmoiz Alatabani
Rok vydání: 2021
Předmět:
Zdroj: Internet of Things ISBN: 9783030764920
DOI: 10.1007/978-3-030-76493-7_8
Popis: Internet of vehicles (IoV) has become an important revolution of intelligent transportation system (ITS). It became an emerging research area as the need for it has increased tremendously. With a great number of applications available, in addition to the intention to improve the quality of life and quality of services, the application of artificial intelligence (AI) techniques would dramatically enhance the performance of the IoV overall system. This chapter will discuss deep learning networks as a type of machine learning use in IoV with influence of Neural Networks (NN), where great amounts of unlabeled data are processed, classified and clustered. Deep learning network approaches i.e., Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Deep Reinforcement Learning (DRL), classification, clustering, and predictive analysis (regression) will briefly discussed in this chapter, in addition to review its ability to obtain better performing IoV applications.
Databáze: OpenAIRE