Results 31 to 40 of about 22,598 (163)

Solar Insolation Prediction through Deep Belief Network

, 2019
El desarrollo continuo de las herramientas computacionales ofrece la posibilidad de realizar procesos con la capacidad de llevar a cabo actividades con mayor eficiencia, exactitud y precisión.
Ruiz Cárdenas, Luis Carlos, Amaya Hurtado, Dario, Jiménez Moreno, Robinson   +2 more
core   +2 more sources

Proposing a new method of image classification based on the AdaBoost deep belief network hybrid method

, 2019
Image classification has different applications. Up to now, various algorithms have been presented for image classification. Each of these method has its own weaknesses and strengths.
Bagherzadeh, Jamshid; Urmia University, Asil, Hasan; Urmia University   +1 more
core   +1 more source

Sequence-discriminative training of deep neural networks

, 2013
Sequence-discriminative training of deep neural networks (DNNs) is investigated on a 300 hour American English conversational telephone speech task. Different sequence-discriminative criteria ndash;- maximum mutual information (MMI), minimum phone error (
Ghoshal, Arnab, Veselý, Karel, Povey, Daniel, Burget, Lukás   +3 more
core  

Effects of Sparse Initialization in Deep Belief Networks

Computer Science, 2015
Deep neural networks are often trained in two phases: first hidden layers are pretrained in an unsupervised manner and then network is fine-tuned with error backpropagation. Pretraining is often carried out using Deep Belief Networks (DBNs), with initial weights set to small random values.
Karol Grzegorczyk, Marcin Kurdziel, Piotr Iwo Wójcik   +2 more
openaire   +2 more sources

The Deep Belief and Self-Organizing Neural Network as a Semi-Supervised Classification Method for Hyperspectral Data

, 2017
Hyperspectral data is not linearly separable, and it has a high characteristic dimension. This paper proposes a new algorithm that combines a deep belief network based on the Boltzmann machine with a self-organizing neural network.
Nan Yu, Quanxin Wang, Qingjian Li, Suling Jia, Wei Lan, Ke Li   +5 more
core   +1 more source

Robust Sound Event Classification using Deep Neural Networks [PDF]

, 2015
The automatic recognition of sound events by computers is an important aspect of emerging applications such as automated surveillance, machine hearing and auditory scene understanding.
Song, Yan, McLoughlin, Ian Vince, Xie, Zhi-Peng, Xiao, Wei, Zhang, Hao-min   +4 more
core   +1 more source

Foreign exchange prediction and trading using deep belief neural network

, 2020
Foreign exchange rate prediction is never an easy task due to the size of the foreign exchange market and the different influences in the market. In this report, neural network is used as a modelling technique to predict currency prices.
Huang, Melvin Jin Wei
core  

Speaker Recognition using Deep Belief Networks

CoRR, 2018
Short time spectral features such as mel frequency cepstral coefficients(MFCCs) have been previously deployed in state of the art speaker recognition systems, however lesser heed has been paid to short term spectral features that can be learned by generative learning models from speech signals.
Adrish Banerjee, Akash Dubey, Abhishek Menon, Shubham Nanda, Gora Chand Nandi   +4 more
openaire   +2 more sources

Sentiment Analysis on Twitter Using Deep Belief Network Optimized with Particle Swarm Optimization

Deep Belief Network is a type of artificial neural network that is widely used in machine learning and deep learning tasks that allows it to learn hierarchical representations of the input data.
Muhammad Aldi Rizqullah, Irma Amelia Dewi   +1 more
core   +1 more source

Development of Deep Belief Network for Tool Faults Recognition. [PDF]

Sensors (Basel), 2023
Kale AP, Wahul RM, Patange AD, Soman R, Ostachowicz W.   +4 more
europepmc   +1 more source