Results 11 to 20 of about 22,598 (163)
Single and combined fault diagnosis of reciprocating compressor valves using a hybrid deep belief network [PDF]
, 2017 In this paper, a hybrid deep belief network is proposed to diagnose single and combined faults of suction and discharge valves in a reciprocating compressor.
Faisal AlThobiani +12 more
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Modular deep belief networks that do not forget [PDF]
The 2011 International Joint Conference on Neural Networks, 2011 Deep belief networks (DBNs) are popular for learning compact representations of high-dimensional data. However, most approaches so far rely on having a single, complete training set. If the distribution of relevant features changes during subsequent training stages, the features learned in earlier stages are gradually forgotten.
Pape L. +3 more
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Deep Belief Networks for Image Denoising
, 2013 ICLR 2014 Conference ...
Mohammad Ali Keyvanrad +2 more
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Reciprocating compressor fault diagnosis using an optimized convolutional deep belief network
, 2021 © The Author(s) 2020. This article proposes an optimized convolutional deep belief network for fault diagnosis of reciprocating compressors.
Ma, B, Ji, J, Zhang, Y
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Hyperspectral Data Feature Extraction Using Deep Belief Network
, 2016 Hyperspectral data has rich spectrum information, strong correlation between bands and high data redundancy. Feature band extraction of hyperspectral data is a prerequisite and an important basis for the subsequent study of classification and target ...
Jiang Xinhua +3 more
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Improved Classification Based on Deep Belief Networks [PDF]
, 2020 For better classification generative models are used to initialize the model and model features before training a classifier. Typically it is needed to solve separate unsupervised and supervised learning problems. Generative restricted Boltzmann machines and deep belief networks are widely used for unsupervised learning. We developed several supervised
Jaehoon Koo, Diego Klabjan
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Structure of deep belief network based on dynamic supervision.
, 2016 Structure of deep belief network based on dynamic supervision.
Yajun Zhang (1543207) +2 more
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Deep Belief Network and Auto-Encoder for Face Classification [PDF]
, 2022 The Deep Learning models have drawn ever-increasing research interest owing to their intrinsic capability of overcoming the drawback of traditional algorithm.
Aouatif, Amine +3 more
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Short-Term Traffic Flow Prediction with Structure-Optimized Deep Belief Network
, 2022 This paper proposes a structure-optimized deep belief network method for short-term traffic flow forecast, which is used to solve the problems of too simple training data in deep learning short-term traffic flow forecast and random selection of model ...
Liu, Yong
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Sentimen Analisis Tweet Berbahasa Indonesia Dengan Deep Belief Network
, 2017 Sentiment analysis is a computational research of opinion sentiment and emotion which is expressed in textual mode. Twitter becomes the most popular communication device among internet users. Deep Learning is a new area of machine learning research.
Edi Winarko +3 more
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