Výsledky vyhledávání - "Nonnegativity-constrained autoencoder"

Driver identification based on hidden feature extraction by using adaptive nonnegativity-constrained autoencoder Autor 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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Milling tool condition monitoring for difficult-to-cut materials based on NCAE and IGWO-SVM Autor Wang, Siqi, Yan, Shichao, Sun, Yuwen

“… To handle this issue, this paper proposed a novel method for monitoring tool wear conditions based on the nonnegativity-constrained autoencoder (NCAE…”
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Driving Safety Risk Prediction Using Cost-Sensitive With Nonnegativity-Constrained Autoencoders Based on Imbalanced Naturalistic Driving Data Autor Chen, Jie, Wu, ZhongCheng, Zhang, Jun

“… identification accuracy, long prediction times, and poor applicability. We first propose using a three-layer L 1 /L 2 -nonnegativity-constrained autoencoder to adaptively…”
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Deep Learning of Part-Based Representation of Data Using Sparse Autoencoders With Nonnegativity Constraints Autor Hosseini-Asl, Ehsan, Zurada, Jacek M., Nasraoui, Olfa

“… (nonnegativity-constrained autoencoder), that learns features that show part-based representation of data…”
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Cross-covariance regularized autoencoders for nonredundant sparse feature representation Autor Chen, Jie, Wu, ZhongCheng, Zhang, Jun, Li, Fang, Li, WenJing, Wu, ZiHeng

“… Existing feature representation algorithms based on the sparse autoencoder and nonnegativity-constrained autoencoder tend to produce duplicative encoding and decoding receptive fields, which leads…”
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Deep Learning of Nonnegativity-Constrained Autoencoders for Enhanced Understanding of Data Autor 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 Nonnegativity Constrained Autoencoder (NCSAE…”
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Nonredundant sparse feature extraction using autoencoders with receptive fields clustering Autor Ayinde, Babajide O., Zurada, Jacek M.

“…This paper proposes new techniques for data representation in the context of deep learning using agglomerative clustering. Existing autoencoder-based data…”
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