Autoencoder-based unsupervised clustering and hashing
Sign Up to like & getrecommendations! Published in 2020 at "Applied Intelligence"
DOI: 10.1007/s10489-020-01797-y
Abstract: Faced with a large amount of data and high-dimensional data information in a database, the existing exact nearest neighbor retrieval methods cannot obtain ideal retrieval results within an acceptable retrieval time. Therefore, researchers have begun… read more here.
Keywords: autoencoder based; based unsupervised; clustering hashing; unsupervised clustering ... See more keywords
An autoencoder based formulation for compressed sensing reconstruction.
Sign Up to like & getrecommendations! Published in 2018 at "Magnetic resonance imaging"
DOI: 10.1016/j.mri.2018.06.003
Abstract: This work proposes a new formulation for image reconstruction based on the autoencoder framework. The work follows the adaptive approach used in prior dictionary and transform learning based reconstruction techniques. Existing autoencoder based reconstructions are… read more here.
Keywords: reconstruction; autoencoder based; based formulation; autoencoder ... See more keywords
Autoencoder-based detection of near-surface defects in ultrasonic testing.
Sign Up to like & getrecommendations! Published in 2021 at "Ultrasonics"
DOI: 10.1016/j.ultras.2021.106637
Abstract: Defect detection during pulse-echo ultrasonic testing (UT) is challenging when defects are located in a dead zone where the echoes from the defects are overshadowed by disturbances from the initial ringing signal of the UT… read more here.
Keywords: autoencoder based; near surface; ultrasonic testing; surface defects ... See more keywords
Autoencoder based blind source separation for photoacoustic resolution enhancement
Sign Up to like & getrecommendations! Published in 2020 at "Scientific Reports"
DOI: 10.1038/s41598-020-78310-5
Abstract: Photoacoustics is a promising technique for in-depth imaging of biological tissues. However, the lateral resolution of photoacoustic imaging is limited by size of the optical excitation spot, and therefore by light diffraction and scattering. Several… read more here.
Keywords: autoencoder based; resolution; separation; resolution enhancement ... See more keywords
Autoencoder-Based Recommender System Exploiting Natural Noise Removal
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3262026
Abstract: Collaborative filtering (CF) is a widely used technique in recommender systems by automatically predicting the user’s latent interests based on many users’ historical rating data. To improve the performance of the CF-based recommender systems, users’… read more here.
Keywords: system; autoencoder based; noise; based recommender ... See more keywords
3D-CNN and Autoencoder-Based Gas Detection in Hyperspectral Images
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2023.3235781
Abstract: The detection of gas emission levels is a crucial problem for ecology and human health. Hyperspectral image analysis offers many advantages over traditional gas detection systems with its detection capability from safe distances. Observing that… read more here.
Keywords: autoencoder based; gas; hyperspectral images; gas detection ... See more keywords
A Novel Average Autoencoder-Based Amplify-and-Forward Relay Networks With Hardware Impairments
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Cognitive Communications and Networking"
DOI: 10.1109/tccn.2022.3164901
Abstract: In this paper, we propose a novel Average autoencoder (AE)-based amplify-and-forward (AF) relay networks impacted by the I/Q imbalance (IQI) and additional hardware impairments (AHI), where the source and destination nodes are equipped with neural… read more here.
Keywords: autoencoder based; average autoencoder; novel average; relay ... See more keywords
Variational Autoencoder-Based Metamodeling for Multi-Objective Topology Optimization of Electrical Machines
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Magnetics"
DOI: 10.1109/tmag.2022.3163972
Abstract: Conventional magneto-static finite element (FE) analysis of electrical machine design is time-consuming and computationally expensive. Since each machine topology has a distinct set of parameters, design optimization is commonly performed independently. This article presents a… read more here.
Keywords: topology; autoencoder based; topology optimization; variational autoencoder ... See more keywords
Field experiment on a PSC-I bridge for convolutional autoencoder-based damage detection
Sign Up to like & getrecommendations! Published in 2020 at "Structural Health Monitoring"
DOI: 10.1177/1475921720926267
Abstract: In this study, a field experiment was performed for damage detection on a PSC-I bridge based on a convolutional autoencoder using the damage detection approach proposed in a previous study by the authors. The field… read more here.
Keywords: autoencoder based; damage detection; detection; convolutional autoencoder ... See more keywords
Toward Explainable AutoEncoder-Based Diagnosis of Dynamical Systems
Sign Up to like & getrecommendations! Published in 2023 at "Algorithms"
DOI: 10.3390/a16040178
Abstract: Autoencoders have been used widely for diagnosing devices, for example, faults in rotating machinery. However, autoencoder-based approaches lack explainability for their results and can be hard to tune. In this article, we propose an explainable… read more here.
Keywords: autoencoder based; autoencoder; diagnosis; explainable autoencoder ... See more keywords
Anomaly Detection for Sensor Signals Utilizing Deep Learning Autoencoder-Based Neural Networks
Sign Up to like & getrecommendations! Published in 2023 at "Bioengineering"
DOI: 10.3390/bioengineering10040405
Abstract: Anomaly detection is a significant task in sensors’ signal processing since interpreting an abnormal signal can lead to making a high-risk decision in terms of sensors’ applications. Deep learning algorithms are effective tools for anomaly… read more here.
Keywords: autoencoder based; neural networks; autoencoder; deep learning ... See more keywords