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What is Recurrent Neural Network

Chapter 3
Histopathological Image Analysis in Medical Decision Making
A recurrent neural network is an artificial neural network that has connections between the units which do form a closed directed cycle.
Published in Chapter:
Medical Image Lossy Compression With LSTM Networks
Nithin Prabhu G. (JSS Science and Technology University, India), Trisiladevi C. Nagavi (JSS Science and Technology University, India), and Mahesha P. (JSS Science and Technology University, India)
Copyright: © 2019 |Pages: 22
DOI: 10.4018/978-1-5225-6316-7.ch003
Abstract
Medical images have a larger size when compared to normal images. There arises a problem in the storage as well as in the transmission of a large number of medical images. Hence, there exists a need for compressing these images to reduce the size as much as possible and also to maintain a better quality. The authors propose a method for lossy image compression of a set of medical images which is based on Recurrent Neural Network (RNN). So, the proposed method produces images of variable compression rates to maintain the quality aspect and to preserve some of the important contents present in these images.
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Chapter 577
Recurrent Neural Networks for Predicting Mobile Device State
ANN that uses previous states for making new predictions.
Published in Chapter: Recurrent Neural Networks for Predicting Mobile Device State; From: Encyclopedia of Information Science and Technology, Fourth Edition
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Chapter 57
Sentiment Analysis Using LSTM
A type of Artificial Neural Network which can use its internal memory to process an input sequence.
Published in Chapter: Sentiment Analysis Using LSTM; From: Encyclopedia of Data Science and Machine Learning
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Chapter 207
Sequence Processing with Recurrent Neural Networks
An artificial neural network with feedback connections. This is in contrast to what happens in a feedforward neural network, where the signal simply passes from the input neurons, through the hidden neurons, to the outputs nodes
Published in Chapter: Sequence Processing with Recurrent Neural Networks; From: Encyclopedia of Artificial Intelligence
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Chapter 16
Efficient End-to-End Asynchronous Time-Series Modeling With Deep Learning to Predict Customer Attrition
A neural network with an added dimension to represent the sequence or time component of sequential or temporal data.
Published in Chapter: Efficient End-to-End Asynchronous Time-Series Modeling With Deep Learning to Predict Customer Attrition; From: Handbook of Research on Methodologies and Applications of Supercomputing
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Chapter 12
Neural Network Applications in Hate Speech Detection
A type of neural network where nodes are connected in a temporal sequence to retain information from the past.
Published in Chapter: Neural Network Applications in Hate Speech Detection; From: Neural Networks for Natural Language Processing
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Chapter 9
Deep Learning Approach for Extracting Catch Phrases from Legal Documents
Deep neural network with recursive operation of giving the output of previous as input for next state so that the inputs and outputs are all dependent to each other.
Published in Chapter: Deep Learning Approach for Extracting Catch Phrases from Legal Documents; From: Neural Networks for Natural Language Processing
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