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What is Recurrent Neural Networks

Chapter 7
Encyclopedia of Information Science and Technology, Fifth Edition
A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes form a directed graph along a temporal sequence. This allows it to exhibit temporal dynamic behavior.
Published in Chapter:
Text-Based Image Retrieval Using Deep Learning
Udit Singhania (Vellore Institute of Technology, India) and B. K. Tripathy (Vellore Institute of Technology, India)
Copyright: © 2021 |Pages: 11
DOI: 10.4018/978-1-7998-3479-3.ch007
Abstract
This chapter is mainly an advanced version of the previous version of the chapter named “An Insight to Deep Learning Architectures” in the encyclopedia. This chapter mainly focusses on giving the insights of information retrieval after the year 2014, as the earlier part has been discussed in the previous version. Deep learning plays an important role in today's era, and this chapter makes use of such deep learning architectures which have evolved over time and have proved to be efficient in image search/retrieval nowadays. In this chapter, various techniques to solve the problem of natural language processing to process text query are mentioned. Recurrent neural nets, deep restricted Boltzmann machines, general adversarial nets have been discussed seeing how they revolutionize the field of information retrieval.
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Chapter 7
A Survey on Network Intrusion Detection Using Deep Generative Networks for Cyber-Physical Systems
A recurrent neural network is a type of ANN commonly used in speech recognition and natural language processing.
Published in Chapter: A Survey on Network Intrusion Detection Using Deep Generative Networks for Cyber-Physical Systems; From: Artificial Intelligence Paradigms for Smart Cyber-Physical Systems
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Chapter 19
Question Answering Chatbot Using Memory Networks
In a recurrent neural network the output of the previous node is used as an input in the current node. This can help predict the next step for the algorithm.
Published in Chapter: Question Answering Chatbot Using Memory Networks; From: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry
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Chapter 11
Time Series Forecasting in Retail Sales Using LSTM and Prophet
A class of neural networks that uses feedback loops to model temporal behavior in training data.
Published in Chapter: Time Series Forecasting in Retail Sales Using LSTM and Prophet; From: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry
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Chapter 21
Application of Neural Networks in Animal Science
Neural models where the synaptic weights contain feedback. This network exhibits dynamic temporal behaviour.
Published in Chapter: Application of Neural Networks in Animal Science; From: Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
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Chapter 9
Locally Recurrent Neural Networks and Their Applications
Architectures that incorporate feedback connections among the layers of the network, or those that do not have straightforward layered input-output architecture but instead the inputs flow forth and back among the nodes of the network
Published in Chapter: Locally Recurrent Neural Networks and Their Applications; From: Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
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