Affiliation:
1. Illinois Institute of Technology, USA
2. VIT University, India
Abstract
Deep learning and Artificial intelligence (AI) have been trending these days due to the capability and state-of-the-art results that they provide. They have replaced some highly skilled professionals with neural network-powered AI, also known as deep learning algorithms. Deep learning majorly works on neural networks. This chapter discusses about the working of a neuron, which is a unit component of neural network. There are numerous techniques that can be incorporated while designing a neural network, such as activation functions, training, etc. to improve its features, which will be explained in detail. It has some challenges such as overfitting, which are difficult to neglect but can be overcome using proper techniques and steps that have been discussed. The chapter will help the academician, researchers, and practitioners to further investigate the associated area of deep learning and its applications in the autonomous vehicle industry.
Reference17 articles.
1. Abraham, A. (2005). 129: Artificial Neural Networks. Handbook of Measuring System Design.
2. End-to-end learning for lane keeping of self-driving cars
3. Cogswell, M., Ahmed, F., Girshick, R., Zitnick, L., & Batra, D. (2015). Reducing Overfitting in Deep Networks by Decorrelating Representations. arXiv:1511.06068
4. From Pixels to Actions: Learning to Drive a Car with Deep Neural Networks
5. Hu, Xu, Xiao, Chen, He, Qin, & Heng. (2018). SINet: A Scale-insensitive Convolutional Neural Network for Fast Vehicle Detection. IEEE Transactions on Intelligent Transportation Systems.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. New Recommendation System Based on Students' Engagement Prediction Using CNN to Optimize E-Learning;International Journal of Organizational and Collective Intelligence;2022-10-21
2. Neural Network for Channel Frequency Response Estimation in OFDM Communication Systems;2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T);2022-10-10
3. Comprehensive Overview of Autonomous Vehicles and Their Security Against DDoS Attacks;Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity;2022-06-24
4. Using Deep Analysis of Driver Behavior for Vehicle Theft Detection and Recovery;2021 22nd International Arab Conference on Information Technology (ACIT);2021-12-21