Suchergebnisse - Constrained autoencoder*

Recognition of multivariate geochemical anomalies using a geologically-constrained variational autoencoder network with spectrum separable module – A case study in Shangluo District, China von Zhao, Bo, Zhang, Dehui, Tang, Panpan, Luo, Xiaoyan, Wan, Haoming, An, Lin

“… This study has developed a novel variational autoencoder architecture by incorporating the spectrum separable module, termed SSM-VAE, so as to recognize the multi-mineral-species geochemical patterns …”
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Autoencoder Constrained Clustering With Adaptive Neighbors von Li, Xuelong, Zhang, Rui, Wang, Qi, Zhang, Hongyuan

“… , autoencoder constrained clustering with adaptive neighbors (ACC_AN), is developed. The proposed method not only can adaptively investigate the nonlinear structure of data …”
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Slow feature‐constrained decomposition autoencoder: Application to process anomaly detection and localization von Jia, Mingwei, Jiang, Lingwei, Hu, Junhao, Liu, Yi, Chen, Tao

“… To address this challenge, we propose a slow feature‐constrained decomposition autoencoder (SFC‐DAE …”
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A multi‐feature space constrained stacked autoencoder and its application for uncertain process monitoring von Yang, Jiandong, Wang, Chenhao, Yu, Jianbo, Yan, Xuefeng

“… To mitigate these issues, we propose a novel process monitoring method based on a multi‐feature space constrained stacked autoencoder (MFSCSAE …”
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AEGCN: An Autoencoder-Constrained Graph Convolutional Network von Ma, Mingyuan, Na, Sen, Wang, Hongyu

“… We propose a novel neural network architecture, called autoencoder-constrained graph convolutional network, to solve node classification task on graph domains …”
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Subspace clustering using a low-rank constrained autoencoder von Chen, Yuanyuan, Zhang, Lei, Yi, Zhang

“… Many data representation methods have been developed in recent years. Typical among them are low-rank representation (LRR) and an autoencoder …”
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A computer‐aided diagnostic system for detecting diabetic retinopathy in optical coherence tomography images von ElTanboly, Ahmed, Ismail, Marwa, Shalaby, Ahmed, Switala, Andy, El‐Baz, Ayman, Schaal, Shlomit, Gimel’farb, Georgy, El‐Azab, Magdi

“… Purpose Detection (diagnosis) of diabetic retinopathy (DR) in optical coherence tomography (OCT) images for patients with type 2 diabetes, but almost …”
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Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders von Georgiev, Dimitar, Fernández-Galiana, Álvaro, Vilms Pedersen, Simon, Papadopoulos, Georgios, Xie, Ruoxiao, Stevens, Molly M, Barahona, Mauricio

“… often struggle with complex mixture scenarios encountered in practice. Here, we develop hyperspectral unmixing algorithms based on autoencoder neural networks …”
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Deep Learning of Constrained Autoencoders for Enhanced Understanding of Data von Ayinde, Babajide O., Zurada, Jacek M.

“… This is especially prominent when multilayer deep learning architectures are used. This paper demonstrates how to remove these bottlenecks within the architecture of non-negativity constrained autoencoder …”
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Driver identification based on hidden feature extraction by using adaptive nonnegativity-constrained autoencoder von Chen, Jie, Wu, ZhongCheng, Zhang, Jun

“… identification accuracy and long prediction time. We first propose using an unsupervised three-layer nonnegativity-constrained autoencoder to adaptive search the optimal size of the sliding window, then construct a deep nonnegativity-constrained …”
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Constrained Autoencoder-Based Pulse Compressed Thermal Wave Imaging for Sub-Surface Defect Detection von Kaur, Kirandeep, Mulaveesala, Ravibabu, Mishra, Priyanka

“… This paper proposes a novel constrained and regularized autoencoder based thermography approach for sub-surface defect detection in a mild steel specimen …”
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Learning nonlinear projections for reduced-order modeling of dynamical systems using constrained autoencoders von Otto, Samuel E, Macchio, Gregory R, Rowley, Clarence W

“… To begin to address these issues, we introduce a parametric class of nonlinear projections described by constrained autoencoder neural networks in which both the manifold and the projection fibers are learned from data …”
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Improving Channel Charting with Representation -Constrained Autoencoders von Huang, Pengzhi, CastaNeda, Oscar, Gonultas, Emre, Medjkouh, SaId, Tirkkonen, Olav, Goldstein, Tom, Studer, Christoph

“… In this paper, we demonstrate that autoencoder (AE)-based CC can be augmented with side information that is obtained during the CSI acquisition process …”
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Generative adversarial network constrained multiple loss autoencoder: A deep learning‐based individual atrophy detection for Alzheimer's disease and mild cognitive impairment von Shi, Rong, Sheng, Can, Jin, Shichen, Zhang, Qi, Zhang, Shuoyan, Zhang, Liang, Ding, Changchang, Wang, Luyao, Wang, Lei, Han, Ying, Jiang, Jiehui

“… Here, we proposed a framework called generative adversarial network constrained multiple loss autoencoder (GANCMLAE …”
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Driving Safety Risk Prediction Using Cost-Sensitive With Nonnegativity-Constrained Autoencoders Based on Imbalanced Naturalistic Driving Data von Chen, Jie, Wu, ZhongCheng, Zhang, Jun

“… In this paper, we propose a novel cost-sensitive L 1 /L 2 -nonnegativity-constrained deep autoencoder network for driving safety risk prediction …”
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Bubble: a fast single-cell RNA-seq imputation using an autoencoder constrained by bulk RNA-seq data von Chen, Siqi, Yan, Xuhua, Zheng, Ruiqing, Li, Min

“… We propose Bubble, which first identifies dropout events from all zeros based on expression rate and coefficient of variation of genes within cell subpopulation, and then leverages an autoencoder …”
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Learned Design of a Compressive Hyperspectral Imager for Remote Sensing by a Physics-Constrained Autoencoder von Heiser, Yaron, Stern, Adrian

“… We present a novel physics-constrained autoencoder (PyCAE) for the design and optimization of a physically realizable sensing model …”
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Geometry-Based Molecular Generation With Deep Constrained Variational Autoencoder von Li, Chunyan, Yao, Junfeng, Wei, Wei, Niu, Zhangming, Zeng, Xiangxiang, Li, Jin, Wang, Jianmin

“… We proposed GEOM-CVAE, a constrained variational autoencoder based on geometric representation for molecular generation with specific properties, which is protein-context-dependent …”
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Unsupervised Health Indicator Construction by a Novel Degradation-Trend-Constrained Variational Autoencoder and Its Applications von 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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Phy-ChemNODE: an end-to-end physics-constrained autoencoder-NeuralODE framework for learning stiff chemical kinetics of hydrocarbon fuels von Kumar, Tadbhagya, Kumar, Anuj, Pal, Pinaki

“… In this work, a physics-constrained Autoencoder (AE)-NeuralODE framework, termed as PhyChemNODE, is developed for data-driven modeling and temporal emulation of stiff chemical kinetics for complex hydrocarbon fuels, wherein a non-linear AE is employed …”
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