scholarly journals Hand Foot and Mouth Rash Detection Using Deep Convolution Neural Network

2021 ◽  
Author(s):  
Naqibullah Vakili ◽  
Jonathan H. Chan ◽  
Worarat Krathu ◽  
Nipat Phattarakijtham ◽  
Kazuya Hirata
Keyword(s):  
Neural Network ◽  
Computational Intelligence ◽  
Convolution Neural Network ◽  
Joint Symposium ◽  
Foot And Mouth ◽  
Deep Convolution Neural Network ◽  
Research Students ◽  
Young Researchers ◽  
Support Research

<div>This work was presented at the 9th Joint Symposium on Computational Intelligence (JSCI9), organized by the IEEE-CIS Thailand Chapter, that aims to support research students and young researchers, to create a place enabling participants to share and discuss on their research prior to publishing their works. The event was open to all researchers who want to broaden their knowledge in the field of computational intelligence.</div>

scholarly journals Hand Foot and Mouth Rash Detection Using Deep Convolution Neural Network

2021 ◽  
Author(s):  
Naqibullah Vakili ◽  
Jonathan H. Chan ◽  
Worarat Krathu ◽  
Nipat Phattarakijtham ◽  
Kazuya Hirata
Keyword(s):  
Neural Network ◽  
Computational Intelligence ◽  
Convolution Neural Network ◽  
Joint Symposium ◽  
Foot And Mouth ◽  
Deep Convolution Neural Network ◽  
Research Students ◽  
Young Researchers ◽  
Support Research

<div>This work was presented at the 9th Joint Symposium on Computational Intelligence (JSCI9), organized by the IEEE-CIS Thailand Chapter, that aims to support research students and young researchers, to create a place enabling participants to share and discuss on their research prior to publishing their works. The event was open to all researchers who want to broaden their knowledge in the field of computational intelligence.</div>

scholarly journals Learning from Others: Daily COVID-19 Cases Prediction in India using Ensembles of LSTM-RNNs

2021 ◽  
Author(s):  
Debasrita Chakraborty ◽  
Debayan Goswami ◽  
Susmita Ghosh ◽  
Jonathan H. Chan ◽  
Ashish Ghosh
Keyword(s):  
Computational Intelligence ◽  
Joint Symposium ◽  
Research Students ◽  
Learning From Others ◽  
Young Researchers ◽  
Support Research

This work was presented at the 10th Joint Symposium on Computational Intelligence (JSCI10), organized by the IEEE-CIS Thailand Chapter, that aims to support research students and young researchers, to create a place enabling participants to share and discuss on their research prior to publishing their works. The event was open to all researchers who want to broaden their knowledge in the field of computational intelligence.

scholarly journals Learning from Others: Daily COVID-19 Cases Prediction in India using Ensembles of LSTM-RNNs

2021 ◽  
Author(s):  
Debasrita Chakraborty ◽  
Debayan Goswami ◽  
Susmita Ghosh ◽  
Jonathan H. Chan ◽  
Ashish Ghosh
Keyword(s):  
Computational Intelligence ◽  
Joint Symposium ◽  
Research Students ◽  
Learning From Others ◽  
Young Researchers ◽  
Support Research

This work was presented at the 10th Joint Symposium on Computational Intelligence (JSCI10), organized by the IEEE-CIS Thailand Chapter, that aims to support research students and young researchers, to create a place enabling participants to share and discuss on their research prior to publishing their works. The event was open to all researchers who want to broaden their knowledge in the field of computational intelligence.

scholarly journals Handwritten Pashto Characters Dataset for Optical Character Recognition

2021 ◽  
Author(s):  
wahidullah mudaser ◽  
Jonathan H. Chan
Keyword(s):  
Computational Intelligence ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Joint Symposium ◽  
Optical Character ◽  
Research Students ◽  
Young Researchers ◽  
Support Research

<div>This work was presented at the 9th Joint Symposium on Computational Intelligence (JSCI9), organized by the IEEE-CIS Thailand Chapter, that aims to support research students and young researchers, to create a place enabling participants to share and discuss on their research prior to publishing their works. The event was open to all researchers who want to broaden their knowledge in the field of computational intelligence.</div><div><br></div><div><div>The Pashto character database developed in this work is available at <a href="https://github.com/mudaser37/pashtoCharacterDataset" rel="noreferrer noopener" target="_blank">GitHub - mudaser37/pashtoCharacterDataset</a></div></div>

scholarly journals Handwritten Pashto Characters Dataset for Optical Character Recognition

2021 ◽  
Author(s):  
wahidullah mudaser ◽  
Jonathan H. Chan
Keyword(s):  
Computational Intelligence ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Joint Symposium ◽  
Optical Character ◽  
Research Students ◽  
Young Researchers ◽  
Support Research

<div>This work was presented at the 9th Joint Symposium on Computational Intelligence (JSCI9), organized by the IEEE-CIS Thailand Chapter, that aims to support research students and young researchers, to create a place enabling participants to share and discuss on their research prior to publishing their works. The event was open to all researchers who want to broaden their knowledge in the field of computational intelligence.</div><div><br></div><div><div>The Pashto character database developed in this work is available at <a href="https://github.com/mudaser37/pashtoCharacterDataset" rel="noreferrer noopener" target="_blank">GitHub - mudaser37/pashtoCharacterDataset</a></div></div>

An improved deep convolution neural network for predicting the remaining useful life of rolling bearings

2020 ◽  
pp. 1-9
Author(s):  
Yiming Guo ◽  
Hui Zhang ◽  
Zhijie Xia ◽  
Chang Dong ◽  
Zhisheng Zhang ◽  
...  
Keyword(s):  
Neural Network ◽  
Degradation Process ◽  
Rolling Bearing ◽  
Remaining Useful Life ◽  
Convolution Neural Network ◽  
Dual Channel ◽  
Time Domain Data ◽  
Channel Input ◽  
Deep Convolution Neural Network ◽  
Useful Life

The rolling bearing is the crucial component in the rotating machinery. The degradation process monitoring and remaining useful life prediction of the bearing are necessary for the condition-based maintenance. The commonly used deep learning methods use the raw or processed time domain data as the input. However, the feature extracted by these approaches is insufficient and incomprehensive. To tackle this problem, this paper proposed an improved Deep Convolution Neural Network with the dual-channel input from the time and frequency domain in parallel. The proposed methodology consists of two stages: the incipient failure identification and the degradation process fitting. To verify the effectiveness of the method, the IEEE PHM 2012 dataset is adopted to compare the proposed method and other commonly used approaches. The results show that the improved Deep Convolution Neural Network can effectively describe the degradation process for the rolling bearing.

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