Results 21 to 30 of about 64,275 (248)
IEEE Access, 2021 Efficient modeling of high-dimensional data requires extracting only relevant dimensions through feature learning. Unsupervised feature learning has gained tremendous attention due to its unbiased approach, no need for prior knowledge or expensive manual
Chathurika S. Wickramasinghe +2 more
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Applied Sciences, 2020 As defect detection using machine vision is diversifying and expanding, approaches using deep learning are increasing. Recently, there have been much research for detecting and classifying defects using image segmentation, image detection, and image ...
Young-Joo Han, Ha-Jin Yu
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Comparison of methods for correcting outliers in ECG-based biometric identification
Metrology and Measurement Systems, 2020 The aim of this paper is to compare the efficiency of various outlier correction methods for ECG signal processing in biometric applications. The main idea is to correct anomalies in various segments of ECG waveform rather than skipping a corrupted ECG ...
Su Jun +6 more
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Digital Chemical EngineeringAutoencoder-based reduced-order machine learning models have been developed for modeling and predictive control of nonlinear chemical processes with high dimensionality such as discretization of reaction–diffusion processes.
Wallace Gian Yion Tan, Ming Xiao, Zhe Wu
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Self-Net: Lifelong Learning via Continual Self-Modeling
Frontiers in Artificial Intelligence, 2020 Learning a set of tasks over time, also known as continual learning (CL), is one of the most challenging problems in artificial intelligence. While recent approaches achieve some degree of CL in deep neural networks, they either (1) store a new network ...
Jaya Krishna Mandivarapu +2 more
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Reconstruction Residuals Based Long-term Voltage Stability Assessment Using Autoencoders
Journal of Modern Power Systems and Clean Energy, 2020 Real-time voltage stability assessment (VSA) has long been an extensively research topic. In recent years, rapidly mounting deep learning methods have pushed online VSA to a new height that large amounts of learning algorithms are applied for VSA from ...
Haosen Yang, Robert C. Qiu, Houjie Tong
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Quantum autoencoders via quantum adders with genetic algorithms
, 2018 The quantum autoencoder is a recent paradigm in the field of quantum machine learning, which may enable an enhanced use of resources in quantum technologies.
Alvarez-Rodriguez, U. +4 more
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The Optimally Designed Deep Autoencoder-Based Compressive Sensing Framework for 1D and 2D Signals
IEEE AccessThe capacity of Compressive Sensing (CS) to recreate original data from a limited number of samples has led to a surge in attention in recent years.
Irfan Ahmed +3 more
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Group Sparse CNNs for Question Classification with Answer Sets
, 2017 Question classification is an important task with wide applications. However, traditional techniques treat questions as general sentences, ignoring the corresponding answer data.
Huang, Liang +3 more
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Unsupervised Deep Learning for Structural Health Monitoring
Big Data and Cognitive Computing, 2023 In the last few decades, structural health monitoring has gained relevance in the context of civil engineering, and much effort has been made to automate the process of data acquisition and analysis through the use of data-driven methods.
Roberto Boccagna +4 more
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