Search Results - "variational autoencoder (VAE)"

Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design by Mak, Hugo Wai Leung, Han, Runze, Yin, Hoover H. F.

“…In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capability in image generation and dimensionality reduction…”
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A dimensionality reduction algorithm for mapping tokamak operational regimes using a variational autoencoder (VAE) neural network by Wei, Y., Levesque, J.P., Hansen, C.J., Mauel, M.E., Navratil, G.A.

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Developing an Explainable Variational Autoencoder (VAE) Framework for Accurate Representation of Local Circulation in Taiwan by Hsieh, Min‐Ken, Wu, Chien‐Ming

“…This study develops an explainable variational autoencoder (VAE) framework to efficiently generate high…”
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A Variational AutoEncoder (VAE)-based Deep Learning Anomaly Detection Model for Industrial Products with Dynamic Weights Assigned to Loss Function by Kasahara, Shunta Nakata,Takehiro, Nambo, Hidetaka

“… We propose a new model based on the variational autoencoder (VAE), which is a generative model applicable to detection by unsupervised learning…”
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TrajVAE: A Variational AutoEncoder model for trajectory generation by Chen, Xinyu, Xu, Jiajie, Zhou, Rui, Chen, Wei, Fang, Junhua, Liu, Chengfei

“…) and Variational AutoEncoder (VAE) frameworks respectively to generate trajectories. In order of compare the similarity of existing trajectories in our dataset and the generated trajectories, we utilize multiple trajectory similarity metrics. Through several experiments, we demonstrate that our method is more accurate and stable than the baseline…”
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DAEN: Deep Autoencoder Networks for Hyperspectral Unmixing by Su, Yuanchao, Li, Jun, Plaza, Antonio, Marinoni, Andrea, Gamba, Paolo, Chakravortty, Somdatta

“… In the second part of the network, a variational autoencoder (VAE) is employed to perform blind source separation, aimed at obtaining the endmember signatures and abundance fractions simultaneously…”
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Image inpainting based on deep learning: A review by Qin, Zhen, Zeng, Qingliang, Zong, Yixin, Xu, Fan

“…•Classify image inpainting methods based on deep learning from a new perspective.•Summarizes the current research status in the field of image…”
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Chiller Fault Diagnosis Based on VAE-Enabled Generative Adversarial Networks by Yan, Ke, Su, Jianye, Huang, Jing, Mo, Yuchang

“…Artificial intelligence (AI)-enhanced automated fault diagnosis (AFD) has become increasingly popular for chiller fault diagnosis with promising classification…”
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Anomaly detection of power battery pack using gated recurrent units based variational autoencoder by Sun, Changcheng, He, Zhiwei, Lin, Huipin, Cai, Linhui, Cai, Hui, Gao, Mingyu

“…) based variational autoencoder (VAE) (GRU-VAE) framework that detects the early potential anomalies of EV power battery packs…”
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Unsupervised Health Indicator Construction by a Novel Degradation-Trend-Constrained Variational Autoencoder and Its Applications by Qin, Yi, Zhou, Jianghong, Chen, Dingliang

“… The hidden variables of variational autoencoder (VAE) can represent the HI values for a life-cycle dataset with obvious degradation trend…”
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Equivalent Circuit Theory-Assisted Deep Learning for Accelerated Generative Design of Metasurfaces by Wei, Zhaohui, Zhou, Zhao, Wang, Peng, Ren, Jian, Yin, Yingzeng, Pedersen, Gert Frolund, Shen, Ming

“… solution space and improved model training efficiency. Furthermore, we select the variational autoencoder (VAE…”
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Anomaly Detection for Solder Joints Using β-VAE by Ulger, Furkan, Yuksel, Seniha Esen, Yilmaz, Atila

“…In the assembly process of printed circuit boards (PCBs), most of the errors are caused by solder joints in surface mount devices (SMDs). In the literature,…”
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Dynamic prediction of aluminum alloy fatigue crack growth rate based on class incremental learning and multi-dimensional variational autoencoder by Peng, Yufeng, Zhang, Yongzhen, Zhang, Lijun, Yao, Leijiang, Tong, Xiaoyan, Guo, Xingpeng

“…) integrates mechanical, environmental, and material features using variational autoencoders (VAE…”
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Explainable fault detection and diagnosis in HVAC systems using a Koopman operator with normal data by Park, Kyoung-Su, Kim, Jin Hong, Park, Cheol Soo

“… The framework uses a Koopman variational autoencoder (VAE) model trained exclusively on fault-free data to lift nonlinear HVAC dynamics into an observable space where the system evolution…”
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Deep Variational Autoencoder Classifier for Intelligent Fault Diagnosis Adaptive to Unseen Fault Categories by He, Anqi, Jin, Xiaoning

“…With the rapid development of artificial intelligence (AI) in recent years, fault diagnostics for industrial applications have leaped toward partially or fully…”
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Missing data imputation and sensor self-validation towards a sustainable operation of wastewater treatment plants via deep variational residual autoencoders by Ba-Alawi, Abdulrahman H., Loy-Benitez, Jorge, Kim, SangYun, Yoo, ChangKyoo

“… to false alarms and inaccurate imputations. In this study, an inclusive framework for missing data imputation and sensor self-validation based on integrating variational autoencoders (VAE…”
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Temporal Network Embedding for Link Prediction via VAE Joint Attention Mechanism by Jiao, Pengfei, Guo, Xuan, Jing, Xin, He, Dongxiao, Wu, Huaming, Pan, Shirui, Gong, Maoguo, Wang, Wenjun

“…Network representation learning or embedding aims to project the network into a low-dimensional space that can be devoted to different network tasks. Temporal…”
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Intrusion Detection System After Data Augmentation Schemes Based on the VAE and CVAE by Liu, Chang, Antypenko, Ruslan, Sushko, Iryna, Zakharchenko, Oksana

“…Industrial Internet of Things (IoT) is the most rapidly developing industry in the current IoT industry, and the intrusion detection system (IDS) remains one…”
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A variational autoencoder inspired unsupervised remote sensing image super resolution method with multi-degradation by Zhang, Ning, Wang, Yongcheng, Li, Gang, Xu, Dongdong, Werner, Martin

“… Inspired by variational autoencoders (VAEs) that model data distributions through latent representations, this paper proposes a VAE framework for unsupervised remote sensing image (RSI) SR…”
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An ensemble method for investigating maritime casualties resulting in pollution occurrence: Data augmentation and feature analysis by Li, Duowei, Wong, Yiik Diew, Chen, Tianyi, Wang, Nanxi, Yuen, Kum Fai

“…•Prediction of maritime casualties resulting in pollution occurrence powered by AI technology.•Employment of VAE based data augmentation to address data…”
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