TY - CHAP
T1 - Neural Networks and Deep Learning
AU - Shanthamallu, Uday Shankar
AU - Spanias, Andreas
N1 - Publisher Copyright:
© 2022, Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - In this chapter, a brief introduction to the field of artificial neural networks is provided with a focus on deep learning [9], neural network training, and different architectures. Artificial neural networks are powerful pattern recognition machines, and they have proved to be the most successful. Neural networks and deep learning are quite successful at end-to-end learning, and they do not require feature engineering as in traditional machine learning techniques such as SVM and decision trees. Deep learning has achieved unprecedented results in various fields, including signal processing [143, 144], computer vision [145], speech and audio processing [146], and natural language processing [147, 148].
AB - In this chapter, a brief introduction to the field of artificial neural networks is provided with a focus on deep learning [9], neural network training, and different architectures. Artificial neural networks are powerful pattern recognition machines, and they have proved to be the most successful. Neural networks and deep learning are quite successful at end-to-end learning, and they do not require feature engineering as in traditional machine learning techniques such as SVM and decision trees. Deep learning has achieved unprecedented results in various fields, including signal processing [143, 144], computer vision [145], speech and audio processing [146], and natural language processing [147, 148].
UR - http://www.scopus.com/inward/record.url?scp=85139441542&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85139441542&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-03758-0_5
DO - 10.1007/978-3-031-03758-0_5
M3 - Chapter
AN - SCOPUS:85139441542
T3 - Synthesis Lectures on Signal Processing
SP - 43
EP - 57
BT - Synthesis Lectures on Signal Processing
PB - Springer Nature
ER -