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Journal ArticleDOI

A new approach of ECG steganography and prediction using deep learning

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TLDR
To reduce the computational complexity and execution time, encryption was performed in time domain signal, using a new approach and it was observed that this algorithm provided better result among other frequency domain techniques and recently published works.
About
This article is published in Biomedical Signal Processing and Control.The article was published on 2021-02-01. It has received 19 citations till now. The article focuses on the topics: Steganography & Signal-to-noise ratio.

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Citations
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Journal ArticleDOI

Metaverse-Powered Experiential Situational English-Teaching Design: An Emotion-Based Analysis Method

Hongyu Guo, +1 more
TL;DR: Experimental data analysis of the three kinds of learning activities shows that metaverse-powered experiential situational English teaching can promote the improvement of students’ sense of interactivity, immersion, and cognition, and the accuracy and analysis time of CNN–RNN fusion model is much higher than that of baselines.
Journal ArticleDOI

An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour

TL;DR: The Modified Sunflower Optimization (MSFO) algorithm is hybrid along with LBM which optimally selects the parameters that maximize the performance of tumour growth model.
Journal ArticleDOI

Deep neural network based missing data prediction of electrocardiogram signal using multiagent reinforcement learning

TL;DR: Bidirectional long short-term memory recurrent neural network based prediction of missing segment of ECG signal is accomplished, governed by reinforcement learning (RL) using multiagent, applicable to any single channel ECG signals.
Journal ArticleDOI

Effective compression and classification of ECG arrhythmia by singular value decomposition

TL;DR: In this paper, a simple but efficient method utilizing singular value decomposition (SVD) to decompose ECG signals, then applied the decompressed data to a convolutional neural network (CNN) and supporting vector machine (SVM) for classification.
Journal ArticleDOI

An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour

TL;DR: In this paper , the Modified Sunflower Optimization (MSFO) algorithm is hybrid along with Lattice Boltzmann Method (LBM) which optimally selects the parameters that maximize the performance of tumour growth model.
References
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Journal ArticleDOI

Long short-term memory

TL;DR: A novel, efficient, gradient based method called long short-term memory (LSTM) is introduced, which can learn to bridge minimal time lags in excess of 1000 discrete-time steps by enforcing constant error flow through constant error carousels within special units.
Journal ArticleDOI

A Real-Time QRS Detection Algorithm

TL;DR: A real-time algorithm that reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width of ECG signals and automatically adjusts thresholds and parameters periodically to adapt to such ECG changes as QRS morphology and heart rate.
Proceedings Article

On the importance of initialization and momentum in deep learning

TL;DR: It is shown that when stochastic gradient descent with momentum uses a well-designed random initialization and a particular type of slowly increasing schedule for the momentum parameter, it can train both DNNs and RNNs to levels of performance that were previously achievable only with Hessian-Free optimization.
Journal ArticleDOI

Recommendations for the Standardization and Interpretation of the Electrocardiogram

TL;DR: This statement examines the relation of the resting ECG to its technology to establish standards that will improve the accuracy and usefulness of the ECG in practice and to recommend recommendations for ECG standards.
Book

Steganography in Digital Media: Principles, Algorithms, and Applications

TL;DR: This clear, self-contained guide shows you how to understand the building blocks of covert communication in digital media files and how to apply the techniques in practice, including those of steganalysis, the detection of Steganography.
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