Fundamentals Of Neural Networks Architectures Algorithms And Applications

By Doreen Meier. 2016

683 citations recorded by the source corpus.

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Towards textual data augmentation for neural networks: synonyms and maximum loss (2019, background): “As the author of [12] puts it, the backpropagation algorithm”
Review of job shop scheduling research and its new perspectives under Industry 4.0 (2017, methodology): “After training, application of the network involves only the computations of the feed forward phase (Fausett 1994).”
A Survey on Software Fault Localization (2016, methodology): “Wong and Qi [374] propose a fault localization technique based on a back-propagation (BP) neural network, one of the most popular neural network models in practice [112].”
Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review (2022, background): “There are many various types and architectures of neural networks, each with a basic difference in how they learn; they are well described in the literature [151, 152].”
A Survey of the Usages of Deep Learning for Natural Language Processing (2020, background): “ory Networks: A type of recursive neural network that has been used heavily is the recurrent neural network (RNN) [27], [28].”