Results 11 to 20 of about 75,080 (277)
“Identity Bracelets” for Deep Neural Networks
IEEE Access, 2020 The power of deep learning and the enormous effort and money required to build a deep learning model makes stealing them a hugely worthwhile and highly lucrative endeavor.
Xiangrui Xu, Yaqin Li, Cao Yuan
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Using deep neural network with small dataset to predict material defects
Materials & Design, 2019 Deep neural network (DNN) exhibits state-of-the-art performance in many fields including microstructure recognition where big dataset is used in training.
Shuo Feng, Huiyu Zhou, Hongbiao Dong
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Speaker adaptation using codebook integrated deep neural networks for speech enhancement [PDF]
JASA Express LettersDeep neural network (DNN) based speech enhancement techniques have shown superior performance compared to the traditional speech enhancement approaches in handling nonstationary noise.
B Chidambar, D. Hanumanth Rao Naidu
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Journal of Applied Sciences and Environmental Management, 2023 Reservoirs of natural gas and gas condensate have been proposed as a potential for providing affordable and cleaner energy sources to the global population growth and industrialization expansion simultaneously.
P. U. Abeshi +4 more
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Estimation of Overtopping Discharges with Deep Neural Network(DNN) Method [PDF]
Korea Society of Coastal Disaster Prevention, 2021 An Artificial Intelligence(AI) study was conducted to calculate overtopping discharges for various coastal structures. The Deep Neural Network(DNN), one of the artificial intelligence methods, was employed in the study. The neural network was trained, validated and tested using the EurOtop database containing the experimental data collected from all ...
Changkyum Kim, Insik Chun, Byungcheol Oh
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Flutter speed prediction by using deep learning
Advances in Mechanical Engineering, 2021 Deep learning technology has been widely used in various field in recent years. This study intends to use deep learning algorithms to analyze the aeroelastic phenomenon and compare the differences between Deep Neural Network (DNN) and Long Short-term ...
Yi-Ren Wang, Yi-Jyun Wang
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Do Deep Neural Networks Model Nonlinear Compositionality in the Neural Representation of Human-Object Interactions? [PDF]
, 2019 Visual scene understanding often requires the processing of human-object interactions. Here we seek to explore if and how well Deep Neural Network (DNN) models capture features similar to the brain's representation of humans, objects, and their ...
Agarwal, Sumeet, Jha, Aditi
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An Advanced Decision Tree-Based Deep Neural Network in Nonlinear Data Classification
Technologies, 2023 Deep neural networks (DNNs), the integration of neural networks (NNs) and deep learning (DL), have proven highly efficient in executing numerous complex tasks, such as data and image classification.
Mohammad Arifuzzaman +4 more
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Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets [PDF]
Procedings of the British Machine Vision Conference 2016, 2016 British Machine Vision Conference (BMVC ...
Amthor, Manuel +2 more
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Applied Sciences, 2021 In order to improve the measurement speed and prediction accuracy of unconventional reservoir parameters, the deep neural network (DNN) is used to predict movable fluid percentage of unconventional reservoirs.
Jiuxin Wang +4 more
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