Institution
Ngee Ann Polytechnic
Education•Singapore, Singapore•
About: Ngee Ann Polytechnic is a education organization based out in Singapore, Singapore. It is known for research contribution in the topics: Support vector machine & Deep learning. The organization has 754 authors who have published 1240 publications receiving 50155 citations. The organization is also known as: Politeknik Ngee Ann & Ngee Ann Poly.
Papers published on a yearly basis
Papers
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TL;DR: The various applications of HRV and different linear, frequency domain, wavelet domain, nonlinear techniques used for the analysis of the HRV are discussed.
Abstract: Heart rate variability (HRV) is a reliable reflection of the many physiological factors modulating the normal rhythm of the heart. In fact, they provide a powerful means of observing the interplay between the sympathetic and parasympathetic nervous systems. It shows that the structure generating the signal is not only simply linear, but also involves nonlinear contributions. Heart rate (HR) is a nonstationary signal; its variation may contain indicators of current disease, or warnings about impending cardiac diseases. The indicators may be present at all times or may occur at random-during certain intervals of the day. It is strenuous and time consuming to study and pinpoint abnormalities in voluminous data collected over several hours. Hence, HR variation analysis (instantaneous HR against time axis) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system. Computer based analytical tools for in-depth study of data over daylong intervals can be very useful in diagnostics. Therefore, the HRV signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. In this paper, we have discussed the various applications of HRV and different linear, frequency domain, wavelet domain, nonlinear techniques used for the analysis of the HRV.
2,344 citations
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TL;DR: A new model for automatic COVID-19 detection using raw chest X-ray images is presented and can be employed to assist radiologists in validating their initial screening, and can also be employed via cloud to immediately screen patients.
1,868 citations
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TL;DR: In this work, a 13-layer deep convolutional neural network (CNN) algorithm is implemented to detect normal, preictal, and seizure classes and achieved an accuracy, specificity, and sensitivity of 88.67%, 90.00% and 95.00%, respectively.
1,117 citations
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TL;DR: A 9-layer deep convolutional neural network (CNN) is developed to automatically identify 5 different categories of heartbeats in ECG signals to serve as a tool for screening of ECG to quickly identify different types and frequency of arrhythmicheartbeats.
938 citations
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TL;DR: This study reviews recent advances in UQ methods used in deep learning and investigates the application of these methods in reinforcement learning (RL), and outlines a few important applications of UZ methods.
Abstract: Uncertainty quantification (UQ) plays a pivotal role in reduction of uncertainties during both optimization and decision making processes. It can be applied to solve a variety of real-world applications in science and engineering. Bayesian approximation and ensemble learning techniques are two most widely-used UQ methods in the literature. In this regard, researchers have proposed different UQ methods and examined their performance in a variety of applications such as computer vision (e.g., self-driving cars and object detection), image processing (e.g., image restoration), medical image analysis (e.g., medical image classification and segmentation), natural language processing (e.g., text classification, social media texts and recidivism risk-scoring), bioinformatics, etc. This study reviews recent advances in UQ methods used in deep learning. Moreover, we also investigate the application of these methods in reinforcement learning (RL). Then, we outline a few important applications of UQ methods. Finally, we briefly highlight the fundamental research challenges faced by UQ methods and discuss the future research directions in this field.
809 citations
Authors
Showing all 754 results
Name | H-index | Papers | Citations |
---|---|---|---|
Seeram Ramakrishna | 147 | 1552 | 99284 |
U. Rajendra Acharya | 90 | 570 | 31592 |
Anand Asundi | 50 | 655 | 13212 |
Ram Bilas Pachori | 48 | 182 | 8140 |
Ru San Tan | 42 | 301 | 9470 |
Zhengtao Ding | 40 | 289 | 5172 |
Jen Hong Tan | 36 | 73 | 5434 |
Choo Min Lim | 35 | 57 | 5965 |
Alton Y. K. Chua | 35 | 180 | 4552 |
Oliver Faust | 31 | 109 | 3946 |
Tuti Mariana Lim | 31 | 57 | 3862 |
Aurélio Campilho | 29 | 205 | 5249 |
Peter A. Sopade | 29 | 99 | 2787 |
Yuki Hagiwara | 29 | 56 | 4896 |
Chun-Yang Yin | 28 | 94 | 3646 |