A Deep Learning Approach to Predict the Flow Field and Thermal Patterns of Nonencapsulated Phase Change Materials Suspensions in an Enclosure [PDF]
Journal of Applied and Computational Mechanics, 2022 The flow and heat transfer of a novel type of functional phase change nanofluids, nano-encapsulated phase change suspensions, is investigated in the present study using a deep neural networks framework.
Mohammad Edalatifar +2 more
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Deep Neural Networks and An Application in Health Sciences
Van Tıp Dergisi, 2021 INTRODUCTION: Because there is more than one hidden layer between the input and output layers in the neural network algorithm, it is called "Deep Neural Networks". In the study, the Deep Neural Networks algorithm; different input (number of layers, epoch,
Sadi Elasan
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Survey on Backdoor Attacks and Countermeasures in Deep Neural Network [PDF]
Jisuanji kexue yu tansuo, 2023 The neural network backdoor attack aims to implant a hidden backdoor into the deep neural network, so that the infected model behaves normally on benign test samples, but behaves abnormally on poisoned test samples with backdoor triggers.
QIAN Hanwei, SUN Weisong
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Application of deep learning in recognition of accrued earnings management
Heliyon, 2023 We choose the sample data in Chinese capital market to compare the measurement effect of earnings management with Deep Belief Network, Deep Convolution Generative Adversarial Network, Generalized Regression Neural Network and modified Jones model by ...
Jia Li, Zhoutianyang Sun
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A Novel Deep Neural Network Topology for Parametric Modeling of Passive Microwave Components
IEEE Access, 2020 Artificial neural network technique has gained recognition as a powerful technique in microwave modeling and design. This paper proposes a novel deep neural network topology for parametric modeling of microwave components.
Jing Jin +5 more
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Multi-Parameter Inversion of AIEM by Using Bi-Directional Deep Neural Network
Remote Sensing, 2022 A novel multi-parameter inversion method is proposed for the Advanced Integral Equation Model (AIEM) by using bi-directional deep neural network. There is a very complex nonlinear relationship between the surface parameters (dielectric constant and ...
Yu Wang +5 more
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Offline Handwritten Chinese Character Recognition Based on DBN and CNN Fusion Model
Journal of Harbin University of Science and Technology, 2020 Aiming at the problem that some offline handwritten Chinese characters are similar in shape and it is difficult to extract the feature of characters and the recognition is not accurate, a convolutional neural network and deep belief network fusion model ...
LI Lanying, ZHOU Zhigang, CHEN Deyun
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Spiking Neural Network Based on Multi-Scale Saliency Fusion for Breast Cancer Detection
Entropy, 2022 Deep neural networks have been successfully applied in the field of image recognition and object detection, and the recognition results are close to or even superior to those from human beings.
Qiang Fu, Hongbin Dong
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Burst Pressure Prediction of API 5L X-Grade Dented Pipelines Using Deep Neural Network
Journal of Marine Science and Engineering, 2020 Mechanical damage is recognized as a problem that reduces the performance of oil and gas pipelines and has been the subject of continuous research. The artificial neural network in the spotlight recently is expected to be another solution to solve the ...
Dohan Oh +3 more
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Research on Real-Time Face Recognition Algorithm Based on Lightweight Network
Jisuanji kexue yu tansuo, 2020 In order to achieve high-precision real-time face recognition on embedded and mobile devices, the advant-ages and disadvantages of common networks in face recognition are analyzed, and an efficient deep convolution neural network model Lightfacenet is ...
ZHANG Dian, WANG Haitao, JIANG Ying, CHEN Xing
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