Search Results - "Conditional variational autoencoder"

Intelligent Condition-Based Monitoring of Rotary Machines With Few Samples by Dixit, Sonal, Verma, Nishchal K.

“…Recently, intelligent condition based monitoring systems build on deep learning methods have gained popularity. The success of these methods relies upon the…”
Get full text

Improving the Classification Effectiveness of Intrusion Detection by Using Improved Conditional Variational AutoEncoder and Deep Neural Network by Yang, Yanqing, Zheng, Kangfeng, Wu, Chunhua, Yang, Yixian

“…Intrusion detection systems play an important role in preventing security threats and protecting networks from attacks. However, with the emergence of unknown…”
Get full text

Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT by Lopez-Martin, Manuel, Carro, Belen, Sanchez-Esguevillas, Antonio, Lloret, Jaime

“…The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host’s network. In current…”
Get full text

On IoT intrusion detection based on data augmentation for enhancing learning on unbalanced samples by Zhang, Ying, Liu, Qiang

“…Internet of things (IoT) security is a prerequisite for the rapid development of the IoT to enhance human well-being. Machine learning-based intrusion…”
Get full text

A balanced mineral prospectivity model of Canadian magmatic Ni (± Cu ± Co ± PGE) sulphide mineral systems using conditional variational autoencoders by Nagasingha, Lahiru M.A., Bérubé, Charles L., Lawley, Christopher J.M.

“…With the increasing demand for raw materials, innovative exploration techniques are needed to discover large mineral deposits that are accessible from the…”
Get full text

Learning a Probabilistic Model for Diffeomorphic Registration by Krebs, Julian, Delingette, Herve, Mailhe, Boris, Ayache, Nicholas, Mansi, Tommaso

“…We propose to learn a low-dimensional probabilistic deformation model from data which can be used for the registration and the analysis of deformations. The…”
Get full text

Multi-modal graph convolutional network for vessel trajectory prediction based on cooperative intention enhance using conditional variational autoencoder by Jiang, Junhao, Zuo, Yi, Li, Zhiyuan

“…Advances in maritime instrumentation and measurement (I&M), particularly through the widespread adoption of automatic identification system (AIS), have…”
Get full text

Conditional variational autoencoder with Gaussian process regression recognition for parametric models by Zhang, Xuehan, Jiang, Lijian

“…In this article, we present a data-driven method for parametric models with noisy observation data. Gaussian process regression based reduced order modeling…”
Get full text

Improving Multi-agent Trajectory Prediction using Traffic States on Interactive Driving Scenarios by Vishnu, Chalavadi, Abhinav, Vineel, Roy, Debaditya, Mohan, C. Krishna, Babu, Ch. Sobhan

“…Predicting trajectories of multiple agents in interactive driving scenarios such as intersections, and roundabouts are challenging due to the high density of…”
Get full text

Machine learning-based mechanical performance prediction and design of lattice structures by Liu, Yifan, Huang, Wei, Wang, Zhiyong, Zhang, Jie, Liu, Jiayi

“…•A data-driven framework enables elastic modulus prediction and inverse design of lattice cells.•The designed neural network model achieves superior prediction…”
Get full text

Obstacle Avoidance Learning for Robot Motion Planning in Human-Robot Integration Environments by Hong, Yang, Ding, Zhiyu, Yuan, Yuan, Chi, Wenzheng, Sun, Lining

“…In the human-robot integration environment, it is essential for mobile robots to pass through the crowd and complete the navigation task smoothly. However, the…”
Get full text

Conditional variational autoencoder for query expansion in ad-hoc information retrieval by Ou, Wei, Huynh, Van-Nam

“…Query expansion (QE) is commonly used to improve the performance of traditional information retrieval (IR) models. With the adoption of deep learning in IR…”
Get full text

Molecular generative model based on conditional variational autoencoder for de novo molecular design by Lim, Jaechang, Ryu, Seongok, Kim, Jin Woo, Kim, Woo Youn

“…We propose a molecular generative model based on the conditional variational autoencoder for de novo molecular design. It is specialized to control multiple…”
Get full text

Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Conditional Variational Autoencoders-Particle Filter by Jiao, Ruihua, Peng, Kaixiang, Dong, Jie

“…Accurate prediction of remaining useful life (RUL) is of great significance to the safety and reliability of lithium-ion batteries, which is able to provide…”
Get full text

Design Space Exploration and Explanation via Conditional Variational Autoencoders in Meta-Model-Based Conceptual Design of Pedestrian Bridges by Balmer, Vera, Kuhn, Sophia V., Bischof, Rafael, Salamanca, Luis, Kaufmann, Walter, Perez-Cruz, Fernando, Kraus, Michael A.

“…Today, engineers rely on conventional iterative (often manual) techniques for conceptual design. Emerging parametric models facilitate design space exploration…”
Get full text

CSR: Cascade Conditional Variational Auto Encoder with Socially-aware Regression for Pedestrian Trajectory Prediction by Zhou, Hao, Ren, Dongchun, Yang, Xu, Fan, Mingyu, Huang, Hai

“…•The proposed trajectory prediction method consists of a cascaded CVAE module and a socially aware regression module.•The cascaded CVAE module decouples and…”
Get full text

A boosting resampling method for regression based on a conditional variational autoencoder by Huang, Yang, Liu, Duen-Ren, Lee, Shin-Jye, Hsu, Chia-Hao, Liu, Yang-Guang

“…•Proposes a novel resampling method based on a deep generative model to deal with the imbalanced regression data sets.•Improves the effect of undersampling and…”
Get full text

Bayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models by Djebra, Yanis, Liu, Xiaofeng, Marin, Thibault, Tiss, Amal, Dhaynaut, Maeva, Guehl, Nicolas, Johnson, Keith, Fakhri, Georges El, Ma, Chao, Ouyang, Jinsong

“…Positron Emission Tomography (PET) is a valuable imaging method for studying molecular-level processes in the body, such as hyperphosphorylated tau (ptau)…”
Get full text

Conditional Variational Autoencoder and generative adversarial network-based approach for long-tailed fault diagnosis for the motor system by Huang, Mei, Sheng, Chenxing, Rao, Xiang

“…This study addresses the challenge of diagnosing motor faults in long-tailed data distributions, characterized by dominant healthy states and rare fault types…”
Get full text

An anomaly detection method for gas turbines in power plants using conditional variational autoencoder optimized with self-attention by Chen, Dongchao, Li, Xiuxia, Xu, Jingquan, Wang, Zhong

“…An innovative anomaly detection (AD) framework designed for gas turbines (GTs) in power plants working under variable operating conditions (OCs) was proposed…”
Get full text