Results 31 to 40 of about 298,507 (214)
A research on underwater target recognition neural network for small samples
Xibei Gongye Daxue Xuebao, 2022 In the face of the challenges in the field of marine engineering applications in the new era, the goal of automation, high efficiency and accuracy can be achieved by using deep learning-based neural networks in hydroacoustic engineering.
WU Yanchen, WANG Yingmin
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Parallel orthogonal deep neural network
Neural Networks, 2021 Ensemble learning methods combine multiple models to improve performance by exploiting their diversity. The success of these approaches relies heavily on the dissimilarity of the base models forming the ensemble. This diversity can be achieved in many ways, with well-known examples including bagging and boosting.
Peyman Sheikholharam Mashhadi +2 more
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Prediction of Shear Strength of Ultra High Performance Reinforced Concrete Deep Beams without Stirrups by Neural Network [PDF]
Eurasian Journal of Science and Engineering, 2017 : Shear strength of ultra high performance reinforced concrete deep beams without stirrups predicted by neural network models. The neural network model based on 233 beams from literatures considering different parameters such as span to depth ratio ...
Sinan Abdulkhaleq Yaseen +2 more
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Needle-based deep-neural-network camera [PDF]
Applied Optics, 2021 We experimentally demonstrate a camera whose primary optic is a cannula/needle ( d i a m e t e r = 0.22 m m and l e n g t h = 12.5 m m ) that acts as a ...
Ruipeng Guo, Soren Nelson, Rajesh Menon
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Short-Term Load Forecasting of Natural Gas with Deep Neural Network Regression †
Energies, 2018 Deep neural networks are proposed for short-term natural gas load forecasting. Deep learning has proven to be a powerful tool for many classification problems seeing significant use in machine learning fields such as image recognition and speech ...
Gregory D. Merkel +2 more
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A deep learning-based method for predicting the low-cycle fatigue life of austenitic stainless steel
Materials Research Express, 2023 In modern engineering, predicting the fatigue life of materials is crucial for safety assessment. The relationship between fatigue life and its influencing factors is difficult to predict by traditional methods, and deep learning can achieve great power ...
Hongyan Duan +5 more
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Intuitionistic Fuzzy Deep Neural Network
Mathematics, 2023 The concept of an intuitionistic fuzzy deep neural network (IFDNN) is introduced here as a demonstration of a combined use of artificial neural networks and intuitionistic fuzzy sets, aiming to benefit from the advantages of both methods.
Krassimir Atanassov +2 more
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Deep Petri nets of unsupervised and supervised learning
Measurement + Control, 2020 Artificial intelligence is one of the hottest research topics in computer science. In general, when it comes to the needs to perform deep learning, the most intuitive and unique implementation method is to use neural network.
Yi-Nan Lin +5 more
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Ambient backscatter communication-based smart 5G IoT network
EURASIP Journal on Wireless Communications and Networking, 2021 In this paper, we propose an ambient backscatter communication-based smart 5G IoT network. The network consists of two parts, namely a real-time data transmission system based on ambient backscatter communication and a real-time big data analysis system ...
Qiang Liu +3 more
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Design of an Intelligent Educational Evaluation System Using Deep Learning
IEEE Access, 2023 Nowadays, online education has been a more general demand in context of COVID-19 epidemic. The intelligent educational evaluation systems assisted by intelligent techniques are in urgent demand.
Yan Pei, Genshu Lu
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