Self-supervised learning for electroencephalography
Decades of research have shown machine learning superiority in discovering highly
nonlinear patterns embedded in electroencephalography (EEG) records compared with …
nonlinear patterns embedded in electroencephalography (EEG) records compared with …
Efficient clustering of emails into spam and ham: The foundational study of a comprehensive unsupervised framework
The spread and adoption of spam emails in malicious activities like information and identity
theft, malware propagation, monetary and reputational damage etc. are on the rise with …
theft, malware propagation, monetary and reputational damage etc. are on the rise with …
[HTML][HTML] K-Medoids clustering applications for high-dimensionality multiphase probabilistic power flow
Actual power systems' planning studies require the stochastic modeling of networks due to
their increasing penetration of uncertain parameters, such as probabilistic-nature loads and …
their increasing penetration of uncertain parameters, such as probabilistic-nature loads and …
Deep autoencoders for attribute preserving face de-identification
The mass availability of mobile devices equipped with cameras has lead to increased public
privacy concerns in recent years. Face de-identification is a necessary first step towards …
privacy concerns in recent years. Face de-identification is a necessary first step towards …
Self-Supervised Deep Multiview Spectral Clustering
L Zong, F Miao, X Zhang, W Liang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Multiview spectral clustering has received considerable attention in the past decades and
still has great potential due to its unsupervised integration manner. It is well known that …
still has great potential due to its unsupervised integration manner. It is well known that …
Autoencoder-driven spiral representation learning for gravitational wave surrogate modelling
Recently, artificial neural networks have been gaining momentum in the field of gravitational
wave astronomy, for example in surrogate modelling of computationally expensive …
wave astronomy, for example in surrogate modelling of computationally expensive …
Machine Learning Applications in Gravitational Wave Astronomy
N Stergioulas - Compact Objects in the Universe, 2024 - Springer
Gravitational wave astronomy has emerged as a new branch of observational astronomy,
since the first detection of gravitational waves in 2015. The current number of O (100) …
since the first detection of gravitational waves in 2015. The current number of O (100) …
Detecting salient regions in a bi-temporal hyperspectral scene by iterating clustering and classification
Hyperspectral (HS) images captured from Earth by satellite and aircraft have become
increasingly important in several environmental and ecological contexts (eg agriculture and …
increasingly important in several environmental and ecological contexts (eg agriculture and …
Quantum steganography: Hiding secret messages in images using quantum circuits and sift
HJ Azooz, KB Salah, M Kherallah… - International Journal of …, 2023 - search.proquest.com
In today's era of escalating digital threats and the growing need for safeguarding sensitive
information, this research strives to advance the field of information concealment by …
information, this research strives to advance the field of information concealment by …
Self Supervised Correlation-based Permutations for Multi-View Clustering
R Eisenberg, J Svirsky, O Lindenbaum - arXiv preprint arXiv:2402.16383, 2024 - arxiv.org
Fusing information from different modalities can enhance data analysis tasks, including
clustering. However, existing multi-view clustering (MVC) solutions are limited to specific …
clustering. However, existing multi-view clustering (MVC) solutions are limited to specific …