Results 21 to 30 of about 22,598 (163)

Health assessment method of industrial robot reducer based on deep belief network

, 2021
Industrial robots are the most representative equipment in smart manufacturing system. Reducers, which are one of the key components of industrial robots, account for a significant portion of failures in industrial robots.
Yuan DC(袁德成), Wang K(王锴), Ji CC(季成丞)   +2 more
core  

MODEL DETEKSI SERANGAN SSH-BRUTE FORCE BERDASARKAN DEEP BELIEF NETWORK

, 2023
Deep Belief Networks are deep learning models that utilize stacks of Restricted Boltzmann Machines (RBM) or sometimes Autoencoders. Autoencoder is a neural network model that has the same input and output.
Constantin Menteng, Hanif Al Fatta, Arief Setyanto   +2 more
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PREDIKSI SAHAM MENGGUNAKAN DBN ( DEEP BELIEF NETWORK ) [PDF]

, 2017
Dalam penelitian ini akan dibahas prediksi indeks harga saham dengan metode Deep Belief Network (DBN). Penelitian ini menggunakan indeks saham dari pasar saham Indonesia yaitu Indeks Harga Saham Gabungan (IHSG).
GIALI GHAZALI
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Maximum Entropy Learning with Deep Belief Networks [PDF]

Entropy, 2016
Conventionally, the maximum likelihood (ML) criterion is applied to train a deep belief network (DBN). We present a maximum entropy (ME) learning algorithm for DBNs, designed specifically to handle limited training data. Maximizing only the entropy of parameters in the DBN allows more effective generalization capability, less bias towards data ...
Payton Lin, Szu-Wei Fu, Syu-Siang Wang, Ying-Hui Lai, Yu Tsao 0001   +4 more
openaire   +2 more sources

Object-based Urban Land Use Classification using Deep Belief Network [PDF]

, 2018
Urban land use information is very important for urban planning, regional administration and management. Classification of urban land use from high resolution images remains a challenging task, due to the extreme difficulties in differentiating complex ...
Su Wai Tun, Khin Mo Mo Tun
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A Deep Neural Network for Acoustic-Articulatory Speech Inversion

, 2011
In this work, we implement a deep belief network for the acoustic-articulatory inversion mapping problem. We find that adding up to 3 hidden-layers improves inversion accuracy.
Renals, S., Richmond, K.; id_orcid, Uria, Benigno   +2 more
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Bearing Fault Diagnosis Based on Improved Convolutional Deep Belief Network

, 2020
Mechanical equipment fault detection is critical in industrial applications. Based on vibration signal processing and analysis, the traditional fault diagnosis method relies on rich professional knowledge and artificial experience.
Zhongkui Zhu, Dong Wang, Shuangjie Liu, Jiaqi Xie, Changqing Shen, Xiaofeng Shang   +5 more
core   +1 more source

A lecture transcription system combining neural network acoustic and language models

, 2013
This paper presents a new system for automatic transcription of lectures. The system combines a number of novel features, including deep neural network acoustic models using multi-level adaptive networks to incorporate out-of-domain information, and ...
Hori, C, Bell, P, Swietojanski, P, Wu, Y, Yamamoto, H, McInnes, F, Renals, S   +6 more
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Analog Circuit Fault Diagnosis Based on Adaptive Gaussian Deep Belief Network

, 2018
Aiming at the problem that the traditional intelligent fault diagnosis method is overly dependent on feature extraction and the lack of generalization ability, deep belief network is proposed for the fault diagnosis of the analog circuit; Then, by ...
Ying-chen WANG, DUAN Xiu-sheng, Xiu-sheng DUAN, WANG Ying-chen   +3 more
core   +1 more source

Predicción de radiación solar mediante deep belief network

, 2016
The continued development of computational tools offers the possibility to execute processes with the ability to carry out activities more efficiently, exactness and precision.
Ruiz Cárdenas, Luis Carlos, Amaya Hurtado, Dario, Jiménez Moreno, Robinson   +2 more
core   +1 more source