Artificial Neural Networks: An Introduction (SPIE Tutorial Texts in Optical Engineering, Vol. TT68)

By K. Priddy, P. Keller. 2005

436 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/eb41a7cbd1367a26f222eca2585c56683ddfa8f5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Fan Meng
2. Danial Jahed Armaghani
3. Xianbin Wang
4. Peng Chen
5. Lenan Wu
6. Arash Bahrammirzaee

In Computer Networks and Communications

1. Fan Meng
2. Xianbin Wang
3. Peng Chen
4. Lenan Wu

In Control and Systems Engineering

1. Fan Meng
2. Xianbin Wang
3. Peng Chen
4. Lenan Wu
5. Arash Bahrammirzaee

Citations in the corpus

• Blasting-induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization (2014, background): “However, it has been proven that BP algorithm can easily converge to any local minimum and it cannot guarantee convergence in learning (Lee et al. 1991; Priddy and Keller 2005; Adhikari and Agrawal 2011).”
• Automatic Modulation Classification: A Deep Learning Enabled Approach (2018, positive): “We propose a novel end-to-end DNN enabled AMC [32]– [34], which close approximates the ML-AMC and significantly improves the inference speed.”