Results 41 to 50 of about 34,284 (266)
PRPD data analysis with Auto-Encoder Network [PDF]
E3S Web of Conferences, 2019 Gas Insulated Switchgear (GIS) is related to the stable operation of power equipment. The traditional partial discharge pattern recognition method relies on expert experience to carry out feature engineering design artificial features, which has strong ...
Li Songyuan +5 more
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High Voltage, 2019 In this study, an inter-turn fault diagnosis method is proposed based on deep learning algorithm. 12-channel data is obtained in MATLAB/Simulink as the time-domain monitoring signals and labelled with 16 different fault tags, including both primary and ...
Lian Duan +5 more
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IET Science, Measurement & Technology, 2023 Here, performance of auto‐encoder deep neural networks in detection and isolation of induction motor states (healthy, bearing outer race fault, stator winding short circuit and broken rotor bar) in the presence of unbalanced power supply and electro‐pump
Azadeh Gholaminejad +2 more
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Bias-Induced Point Auto-Encoder and Comparative Analysis of Point Encoder-Decoder Combinations
IEEE Access, 2022 As a combination of a point encoder and a decoder, a point auto-encoder (AE) facilitates the reconstruction and segmentation of the point cloud representation of 3D objects. In this paper, first, we present a novel approach to point decoding, referred to
Sukhan Lee, Wencan Cheng, Yongjun Yang
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Auto-Encoding Molecular Conformations
, 2021 In this work we introduce an Autoencoder for molecular conformations. Our proposed model converts the discrete spatial arrangements of atoms in a given molecular graph (conformation) into and from a continuous fixed-sized latent representation. We demonstrate that in this latent representation, similar conformations cluster together while distinct ...
Winter, Robin +2 more
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, 2023 Thoroughly revised the paper originally titled "Vector-Quantized Graph Auto-Encoder. Implemented comprehensive modifications across all sections. Incorporated additional experiments to enhance the study. Maintained the fundamental structure and essence of the original work, ensuring it remains a continuation of the same ...
Boget, Yoann +2 more
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Two-Stream Spatial-Temporal Auto-Encoder With Adversarial Training for Video Anomaly Detection
IEEE AccessAuto-encoder has been widely used in video anomaly detection which aims to detect abnormal segments in video surveillance. However, the previous auto-encoder methods preferred to reconstruct a model of the normal event that only trains on normal samples ...
Biao Guo +3 more
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A Particle Swarm Optimization-based Flexible Convolutional Auto-Encoder for Image Classification
, 2018 Convolutional auto-encoders have shown their remarkable performance in stacking to deep convolutional neural networks for classifying image data during past several years.
Sun, Yanan +3 more
core +1 more source
Solving Inverse Problems via Auto-Encoders [PDF]
IEEE Journal on Selected Areas in Information Theory, 2020 Compressed sensing (CS) is about recovering a structured signal from its under-determined linear measurements. Starting from sparsity, recovery methods have steadily moved towards more complex structures. Emerging machine learning tools such as generative functions that are based on neural networks are able to learn general complex structures from ...
Pei Peng, Shirin Jalali, Xin Yuan
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