Anomaly Detection on Laminated Composite Plate Using Self-Attention Autoencoder and Gaussian Mixture Model by Olivier Munyaneza, Jung Woo Sohn

“…This issue is mostly inherited from their limited ability to capture small temporal variations in Lamb wave signals and their dependence on shallow architectures that suffer with complex signal distributions, causing the misclassification of damaged signals as healthy data. …”
Get full text

Enhancing parkinson disease detection through feature based deep learning with autoencoders and neural networks by P. Valarmathi, Y. Suganya, K. R. Saranya, S. Shanmuga Priya

“…The deep neural network (DNN) model is trained using the retrieved data, allowing it to effectively distinguish minor variations in voice characteristics that are linked to Parkinson’s disease. …”
Get full text

ALSTNet: Autoencoder fused long‐ and short‐term time‐series network for the prediction of tunnel structure by Bowen Du, Haohan Liang, Yuhang Wang, Junchen Ye, Xuyan Tan, Weizhong Chen

“…As a case study, the presented model was applied to the Nanjing Dinghuaimen tunnel to predict the stain variation on a different time scale in the future.…”
Get full text

OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data. by Xixuan Feng, Shuqin Zhang, Limin Li

“…It captures both cell/spot and gene features using two orthogonally coupled variational graph autoencoders across cell/spot and gene dimensions and combines them by maximizing the similarity between their reconstructed cell/spot features. …”
Get full text

Leveraging autoencoder models and data augmentation to uncover transcriptomic diversity of gingival keratinocytes in single cell analysis by Pradeep Kumar Yadalam, Prabhu Manickam Natarajan, Carlos M. Ardila

“…The Basic AE effectively modeled RNA-seq data complexity compared to Variational and Denoising Autoencoders. This study highlights advanced computational techniques to investigate gingival keratinocytes’ transcriptomic diversity, revealing distinct subpopulations and differential gene expression profiles. …”
Get full text

Urban ecological environment quality evaluation using deep autoencoder integration of multisource remote sensing data by Shengtang Wang, Weizhen Wang, Feinan Xu

“…The results indicated that Beijing's UEEQ exhibited overall stability with localized variations, with 85.7 % of the area remaining unchanged. …”
Get full text

Enhancing Weather Monitoring for Agriculture with Deep Learning: Anomaly Detection in East Java Using LSTM Autoencoder and OCSVM by Maulana Ahsan Fadillah, Yenni Angraini, Rahma Anisa

“…Agricultural productivity in East Java is under threat from unpredictable and harsh weather patterns, particularly rapid variations in sunlight length and rainfall intensity.  …”
Get full text

Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders by Muhammad Sajid, Kaleem Razzaq Malik, Ateeq Ur Rehman, Tauqeer Safdar Malik, Masoud Alajmi, Ali Haider Khan, Amir Haider, Seada Hussen

“…Differences between the two domains, such as significant variations in the scale of visual things and the higher granularity of pixels in images compared to words in the text, make it difficult to transfer Transformer from language to vision. …”
Get full text

Design of Capsule-Shaped All-Terrain Robot: A Perpendicular Track Mobility Solution by Abhishek Sebastian, Vinay Murali, R. Pragna, A. Annis Fathima

“…The variational autoencoder enhances the robot’s ability to detect and correct abnormal movements, improving overall system reliability. …”
Get full text

Multi-Head Graph Attention Adversarial Autoencoder Network for Unsupervised Change Detection Using Heterogeneous Remote Sensing Images by Meng Jia, Xiangyu Lou, Zhiqiang Zhao, Xiaofeng Lu, Zhenghao Shi

“…Heterogeneous remote sensing images, acquired from different sensors, exhibit significant variations in data structure, resolution, and radiometric characteristics. …”
Get full text

Local pattern aware 3D video swin transformer with masked autoencoding for realtime augmented reality gesture interaction by Suli Wang

“…In the gesture classification module, the paper proposes a ViT architecture based on a masked autoencoder. It aligns features at different levels through a dynamic weight fusion strategy and combines the relative total variation map as a self-monitoring element. …”
Get full text

Damage Indicators for Structural Monitoring of Fiber-Reinforced Polymer-Strengthened Concrete Structures Based on Manifold Invariance Defined on Latent Space of Deep Autoencoders by Javier Montes, Juan Pérez, Ricardo Perera

“…New synthetic data with their variations, generated with a variational autoencoder, were encompassed to the trained autoencoder. …”
Get full text

Latent Outlier Exposure in Real-Time Anomaly Detection at the Large Hadron Collider by Thomas Dartnall Stern, Amit Kumar Mishra, James Michael Keaveney

“…Among these is a novel adaptation of the variational autoencoder’s reparameterisation trick, specifically optimised for anomaly detection. …”
Get full text

A novel hybrid machine learning framework for spatio-temporal analysis of reference evapotranspiration in India by Dolon Banerjee, Sayantan Ganguly, Wen-Ping Tsai

“…The study emphasizes the spatial, temporal, and seasonal variations of ETo across the region, highlighting its dependence on climatic factors.…”
Get full text

One-Shot Learning from Prototype Stock Keeping Unit Images by Aleksandra Kowalczyk, Grzegorz Sarwas

Get full text

Spatiotemporal associations between air pollution and emergency room visits for cardiovascular and cerebrovascular diseases in Korea using a multivariate graph autoencoder modeling... by Sohee Wang, Seungpil Jeong, Eunhee Ha

“…Purpose This study aimed to assess the spatiotemporal associations between air pollution and emergency room visits for cardiovascular and cerebrovascular diseases in South Korea using a graph autoencoder (GAE). A multivariate graph-based approach was used to uncover seasonal and regional variations in pollutant–disease relationships. …”
Get full text

MONITORING DATA AGGREGATION OF DYNAMIC SYSTEMS USING INFORMATION TECHNOLOGIES by Dmytro Shevchenko, Mykhaylo Ugryumov, Sergii Artiukh

“…The following tasks were solved: analysis of existing dimensionality reduction approaches, description of the general architecture of vanilla and variational autoencoders, development of their architecture, development of software for training and testing of autoencoders, conducting research on the performance quality of autoencoders for the problem of dimensionality reduction. …”
Get full text

A State-Supervised Model and Novel Anomaly Index for Gas Turbines Blade Fault Detection Under Multi-Operating Conditions by Yuan Xiao, Kun Feng, Dongyan Miao, Peng Zhang, Jiaxin Yang

“…First, a State-Supervised Variational Autoencoder (SS-VAE) model is introduced, which integrates the learning process of turbine operational states into the VAE bypass, enabling it to capture variations in vibration signal data across different operating conditions. …”
Get full text

Efficient Classification and Rapid Processing of Big Data in Power Distribution Networks by Luan Ning, Cheng Li, Wang Dingji, Wang Shuaimei

“…PCA, t-SNE and UMAP and data without dimension reduction are combined with K-means clustering for exploring the potential distribution of samples. Subsequently, variational autoencoder (VAE) is used to extract the hidden features of the data and the dimension reduction methods are applied to the hidden structure of data obtained from VAE. …”
Get full text

BlindFG: Learning Contextual Fishing Trajectories for Unreported Fishing Gear Classification by Changha Lee, Chan-Hyun Youn

Get full text