An Introduction to Neural Networks and Deep Learning
Heung-Il Suk Korea University, Seoul, Republic of Korea
Abstract
Artificial neural networks, conceptually and structurally inspired by neural systems, are of great interest along with deep learning, thanks to their great successes in various fields including medical imaging analysis. In this chapter, we describe the fundamental concepts and ideas of (deep) neural networks and explain algorithmic advances to learn network parameters efficiently by avoiding overfitting. Specifically, this chapter focuses on introducing (i) feed-forward neural networks, (ii) gradient descent-based parameter optimization algorithms, (iii) different types of deep models, (iv) technical tricks ...
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