Results 11 to 20 of about 22,071 (254)
“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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A Wireless Positioning Method Based on Deep Neural Network [PDF]
Jisuanji gongcheng, 2016 To deal with the variant and unpredictable wireless signals,this paper proposes a regressive wireless positioning method based on Deep Neural Network(DNN).It uses a four-layer Deep Neural Network(DNN) structure pre-trained by Stacked Denoising ...
LIU Kan,ZHANG Wei,ZHANG Weidong,ZHANG Youmei,GU Jianjun
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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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The #DNN-Verification Problem: Counting Unsafe Inputs for Deep Neural Networks
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023 Deep Neural Networks are increasingly adopted in critical tasks that require a high level of safety, e.g., autonomous driving. While state-of-the-art verifiers can be employed to check whether a DNN is unsafe w.r.t. some given property (i.e., whether there is at least one unsafe input configuration), their yes/no output is not informative enough for ...
Marzari, Luca +3 more
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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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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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Hybrid-DNNs: Hybrid Deep Neural Networks for Mixed Inputs
CoRR, 2020 Rapid development of big data and high-performance computing have encouraged explosive studies of deep learning in geoscience. However, most studies only take single-type data as input, frittering away invaluable multisource, multi-scale information.
Zhenyu Yuan +3 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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