Results 101 to 110 of about 5,065 (216)

Multi-view-AE: A Python package for multi-view autoencoder models

Journal of Open Source Software, 2023
Ana Lawry Aguila, Alejandra Jayme, Nina Montaña Brown, Vincent Heuveline, André Altmann   +4 more
openaire   +2 more sources

Is Autoencoder Truly Applicable for 3D CT Super-Resolution?

, 2023
Featured by a bottleneck structure, autoencoder (AE) and its variants have been largely applied in various medical image analysis tasks, such as segmentation, reconstruction and de-noising. Despite of their promising performances in aforementioned tasks,
Luo, Weixun, Yang, Guang, Xing, Xiaodan
core  

AE-MCDM: an autoencoder-based multi-criteria decision-making approach for unsupervised feature selection

The Journal of Supercomputing
Feature selection is a fundamental technique for reducing the dimensionality of high-dimensional data by identifying the most relevant features while discarding redundant or irrelevant ones. In unsupervised settings, where labeled data are unavailable and labeling is costly, effective feature selection becomes even more challenging. This paper proposes
Hashemi, Amin, Dowlatshahi, Mohammad Bagher, Farshidi, Siamak, Moradi, Parham   +3 more
openaire   +1 more source

AE-DTNN: Autoencoder–Dense–Transformer Neural Network Model for Efficient Anomaly-Based Intrusion Detection Systems

In this study, we introduce an enhanced hybrid Autoencoder–Dense–Transformer Neural Network (AE-DTNN) model for developing an effective intrusion detection system (IDS) aimed at improving the performance and robustness of threat detection ...
Maggie Mashaly, Hesham Kamal
core   +1 more source

Probabilistic Autoencoder

, 2022
Principal Component Analysis (PCA) minimizes the reconstruction error given a class of linear models of fixed component dimensionality. Probabilistic PCA adds a probabilistic structure by learning the probability distribution of the PCA latent space ...
Böhm, Vanessa, Seljak, Uroš
core  

Model Validation for Multivariate Functional Responses via Autoencoder-Based Dual-Layer Feature Extraction

Mathematics
Model validation for complex simulation models with multivariate functional responses poses significant challenges, as it involves the dual coupling of physical correlations among variables and field correlations in time-series data.
Dengyu Wu, Xiaodong Zhang, Daobo Sun, Haidong Lin, Jinhui Li, Baoqiang Zhang   +5 more
doaj   +1 more source

AE-DD: Autoencoder-Driven Dictionary with Matching Pursuit for Joint ECG Denoising, Compression, and Morphology Decomposition

Background: Electrocardiogram (ECG) signals are crucial for cardiovascular diagnosis, but their analysis face challenges from noise contamination, compression difficulties due to their non-stationary nature, and the inherent complexity of its ...
Fars Samann, Thomas Schanze
core   +1 more source

Leveraging autoencoder models and data augmentation to uncover transcriptomic diversity of gingival keratinocytes in single cell analysis

Scientific Reports
Periodontitis, a chronic inflammatory condition of the periodontium, is associated with over 60 systemic diseases. Despite advancements, precision medicine approaches have had limited success, emphasizing the need for deeper insights into cellular ...
Pradeep Kumar Yadalam, Prabhu Manickam Natarajan, Carlos M. Ardila   +2 more
doaj   +1 more source

Data Augmentation for Text Classification Using Autoencoders

IEEE Access
Deep learning models have greatly improved various natural language processing tasks. However, their effectiveness depends on large data sets, which can be difficult to acquire.
Mustafa Cataltas, Ilyas Cicekli, Nurdan Akhan Baykan   +2 more
doaj   +1 more source

Poster Sessions

HemaSphere, Volume 10, Issue S1, June 2026.
wiley   +1 more source