Results 21 to 30 of about 5,483,449 (298)

Bearing Life Prediction Method Based on Parallel Multichannel Recurrent Convolutional Neural Network

Shock and Vibration, 2021
To extract the time-series characteristics of the original bearing signals and predict the remaining useful life (RUL) more effectively, a parallel multichannel recurrent convolutional neural network (PMCRCNN) is proposed for the prediction of RUL ...
Jianmin Zhou, Sen Gao, Jiahui Li, Wenhao Xiong   +3 more
doaj   +1 more source

Multispectral Pansharpening Based on Multisequence Convolutional Recurrent Neural Network

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Multispectral (MS) pansharpening is defined as the fusion of spatial information in panchromatic (PAN) image and spectral information in MS image. In this work, we propose an MS pansharpening based on multisequence convolutional recurrent neural network (
Peng Wang, Zhongchen He, Ying Zhang, Gong Zhang, Hongchao Liu, Henry Leung   +5 more
doaj   +1 more source

Cursive Text Recognition in Natural Scene Images Using Deep Convolutional Recurrent Neural Network

, 2022
Text recognition in natural scene images is a challenging problem in computer vision. Different than the optical character recognition (OCR), text recognition in natural scene images is more complex due to variations in text size, colors, fonts ...
Asghar Ali Chandio, MD. Asikuzzaman, Mark R. Pickering, Asikuzzaman, MD., Pickering, Mark R., Leghari, Mehwish, Chandio, Asghar Ali, Mehwish Leghari   +7 more
core   +1 more source

SORN : a self-organizing recurrent neural network [PDF]

, 2009
Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing ...
Pipa, Gordon, Andreea Lazar, Triesch, Jochen, Lazar, Andreea, Gordon Pipa, Jochen Triesch   +5 more
core   +1 more source

A convolutional recurrent neural network for strong convective rainfall nowcasting using weather radar data in Southeastern Brazil

Artificial Intelligence in Geosciences, 2022
Strong convective systems and the associated heavy rainfall events can trig-ger floods and landslides with severe detrimental consequences. These events have a high spatio-temporal variability, being difficult to predict by standard meteorological ...
Angelica N. Caseri, Leonardo Bacelar Lima Santos, Stephan Stephany   +2 more
doaj   +1 more source

Convolutional-Recurrent Neural Networks for Speech Enhancement [PDF]

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
ICASSP ...
Han Zhao 0002, Shuayb Zarar, Ivan Tashev, Chin-Hui Lee   +3 more
openaire   +3 more sources

Deep Feature Learning for Disease Risk Assessment Based on Convolutional Neural Network With Intra-Layer Recurrent Connection by Using Hospital Big Data

IEEE Access, 2018
This paper presents the analysis of real-life medical big data obtained from a hospital in central China from 2013 to 2015 for risk assessment of cerebral infarction disease.
Mohd Usama, Belal Ahmad, Jiafu Wan, M. Shamim Hossain, Mohammed F. Alhamid, M. Anwar Hossain   +5 more
doaj   +1 more source

Method for predicting cutter remaining life based on multi-scale cyclic convolutional network

International Journal of Distributed Sensor Networks, 2022
In the process of predicting the remaining cutter life, the deep-learning method such as convolutional neural network does not consider the time correlation of different degradation states, which directly affects the accuracy of the remaining cutter life
Tao Li, Yinquan Yu, Chaoqiang Huang, Jinwen Yang, Yuanchang Zhong, Yong Hao   +5 more
doaj   +1 more source

Recurrent convolutional neural networks for poet identification

Digital Scholarship in the Humanities, 2020
Abstract Deep neural networks have been widely used in various language processing tasks. Recurrent neural networks (RNNs) and convolutional neural networks (CNN) are two common types of neural networks that have a successful history in capturing temporal and spatial features of texts.
Momtazi, Saeedeh, Salami, Dariush
openaire   +4 more sources

Fast Graph Convolutional Recurrent Neural Networks [PDF]

2019 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
This paper proposes a Fast Graph Convolutional Neural Network (FGRNN) architecture to predict sequences with an underlying graph structure. The proposed architecture addresses the limitations of the standard recurrent neural network (RNN), namely, vanishing and exploding gradients, causing numerical instabilities during training.
Sai Kiran Kadambari, Sundeep Prabhakar Chepuri   +1 more
openaire   +3 more sources