Results 21 to 30 of about 22,071 (254)
EEG-Based Emotion Classification Using a Deep Neural Network and Sparse Autoencoder
Frontiers in Systems Neuroscience, 2020 Emotion classification based on brain–computer interface (BCI) systems is an appealing research topic. Recently, deep learning has been employed for the emotion classifications of BCI systems and compared to traditional classification methods improved ...
Junxiu Liu +13 more
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Cylinder Pressure Prediction of An HCCI Engine Using Deep Learning
Chinese Journal of Mechanical Engineering, 2021 Engine tests are both costly and time consuming in developing a new internal combustion engine. Therefore, it is of great importance to predict engine characteristics with high accuracy using artificial intelligence. Thus, it is possible to reduce engine
Halit Yaşar +3 more
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Modeling of Deep Neural Network (DNN) Placement and Inference in Edge Computing [PDF]
2020 IEEE International Conference on Communications Workshops (ICC Workshops), 2020 With the edge computing becoming an increasingly adopted concept in system architectures, it is expected its utilization will be additionally heightened when combined with deep learning (DL) techniques. The idea behind integrating demanding processing algorithms in Internet of Things (IoT) and edge devices, such as Deep Neural Network (DNN), has in ...
Mounir Bensalem +2 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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Predicting oral disintegrating tablet formulations by neural network techniques
Asian Journal of Pharmaceutical Sciences, 2018 Oral disintegrating tablets (ODTs) are a novel dosage form that can Peer review under responsibility of Shenyang Pharmaceutical University. be dissolved on the tongue within 3 min or less especially for geriatric and pediatric patients.
Run Han +3 more
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Metals, 2023 In this study, the tensile and shear strengths of aluminum 6061-differently grooved stainless steel 304 explosive clads are predicted using deep learning algorithms, namely the conventional neural network (CNN), deep neural network (DNN), and recurrent ...
Somasundaram Saravanan +2 more
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Frontiers in Computational Neuroscience, 2022 To classify the texts accurately, many machine learning techniques have been utilized in the field of Natural Language Processing (NLP). For many pattern classification applications, great success has been obtained when implemented with deep learning ...
Sunil Kumar Prabhakar +3 more
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IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022 Assessing the severity level of dysarthria can provide an insight into the patient’s improvement, assist pathologists to plan therapy, and aid automatic dysarthric speech recognition systems.
Amlu Anna Joshy, Rajeev Rajan
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Physics Inspired Deep Neural Networks for Top Quark Reconstruction [PDF]
EPJ Web of Conferences, 2020 Deep neural networks (DNNs) have been applied to the fields of computer vision and natural language processing with great success in recent years. The success of these applications has hinged on the development of specialized DNN architectures that take ...
Greif Kevin, Lannon Kevin
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IEEE Access, 2023 Nowadays, mobile application services face the challenges of high speed, low latency and high reliability. The combination of digital twin (DT) technology and mobile edge computing (MEC) network can effectively solve these challenges.
Siyu Yuan +4 more
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