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Siyang Chen, Yunsheng Zhang, Ke Nie, Xiaoming Li and Weixi Wang
This paper presents an automatic building extraction method which utilizes a photogrammetric digital surface model (DSM) and digital orthophoto map (DOM) with the help of historical digital line graphic (DLG) data. To reduce the need for manual labeling,...
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Aleksandr Alekseev, Leonid Kozhemyakin, Vladislav Nikitin and Julia Bolshakova
This paper aimed to increase accuracy of an Alzheimer?s disease diagnosing function that was obtained in a previous study devoted to application of decision roots to the diagnosis of Alzheimer?s disease. The obtained decision root is a discrete switching...
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Artemiy Belousov, Ivan Kisel, Robin Lakos and Akhil Mithran
Algorithms optimized for high-performance computing, which ensure both speed and accuracy, are crucial for real-time data analysis in heavy-ion physics experiments. The application of neural networks and other machine learning methodologies, which are fa...
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Ebenezer O. Oluwasakin and Abdul Q. M. Khaliq
Artificial neural networks have changed many fields by giving scientists a strong way to model complex phenomena. They are also becoming increasingly useful for solving various difficult scientific problems. Still, people keep trying to find faster and m...
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Roman Rybka, Yury Davydov, Danila Vlasov, Alexey Serenko, Alexander Sboev and Vyacheslav Ilyin
Developing a spiking neural network architecture that could prospectively be trained on energy-efficient neuromorphic hardware to solve various data analysis tasks requires satisfying the limitations of prospective analog or digital hardware, i.e., local...
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Hong-Hua Huang, Jian-Fei Luo, Feng Gan and Philip K. Hopke
Small data sets make developing calibration models using deep neural networks difficult because it is easy to overfit the system. We developed two deep neural network architectures by revising two existing network architectures: the U-Net and the attenti...
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José Felix Zapata Usandivaras, Annafederica Urbano, Michael Bauerheim and Bénédicte Cuenot
Improving the predictive capabilities of reduced-order models for the design of injector and chamber elements of rocket engines could greatly improve the quality of early rocket chamber designs. In the present work, we propose an innovative methodology t...
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Luigi Nele, Giulio Mattera and Mario Vozza
Welding is one of the most complex industrial processes because it is challenging to model, control, and inspect. In particular, the quality inspection process is critical because it is a complex and time-consuming activity. This research aims to propose...
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Sergei Strijhak, Daniil Ryazanov, Konstantin Koshelev and Aleksandr Ivanov
In this article the procedure and method for the ice accretion prediction for different airfoils using artificial neural networks (ANNs) are discussed. A dataset for the neural network is based on the numerical experiment results?obtained through iceFoam...
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Andrew John Poulter and Simon J. Cox
Internet of Things (IoT) devices are becoming ubiquitous, and may be arranged to form formal or ad hoc Command and Control (C2) networks. Such networks typically do not have a mechanism to facilitate the sharing of either data or control inputs. This pap...
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Guangluan Xu, Xiaoke Wang, Yang Wang, Daoyu Lin, Xian Sun and Kun Fu
Link prediction is a task predicting whether there is a link between two nodes in a network. Traditional link prediction methods that assume handcrafted features (such as common neighbors) as the link?s formation mechanism are not universal. Other popula...
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Tushar Ganguli and Edwin K. P. Chong
We present a novel technique for pruning called activation-based pruning to effectively prune fully connected feedforward neural networks for multi-object classification. Our technique is based on the number of times each neuron is activated during model...
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Wen-Chang Cheng, Hung-Chou Hsiao, Yung-Fa Huang and Li-Hua Li
This research proposes a single network model architecture for mask face recognition using the FaceNet training method. Three pre-trained convolutional neural networks of different sizes are combined, namely InceptionResNetV2, InceptionV3, and MobileNetV...
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Chin-Yi Chen and Jih-Jeng Huang
Traditional movie recommendation systems are increasingly falling short in the contemporary landscape of abundant information and evolving user behaviors. This study introduced the temporal knowledge graph recommender system (TKGRS), a ground-breaking al...
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Roei Grimberg, Meir Teitel, Shay Ozer, Asher Levi and Avi Levy
Since leaf temperature (LT) is not a trivial measurement, deep-neural networks (DNN) and machine learning (ML) models were evaluated in this study as tools for estimating foliage temperature. Two DNN methods were used. The first DNN used convolutional la...
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Chongjiao Wang, Changrong Yao, Siguang Zhao, Shida Zhao and Yadong Li
The cost assessment of bridge maintenance is a difficult topic to study, but it is critical for a bridge life cycle cost analysis. The maintenance costs sample database was established in this study according to actual engineering data, and a bridge main...
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Yaping Hao and Qiang Gao
In the stock market, predicting the trend of price series is one of the most widely investigated and challenging problems for investors and researchers. There are multiple time scale features in financial time series due to different durations of impact ...
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Muhammad Sohaib and Jong-Myon Kim
Boiler heat exchange in thermal power plants involves tubes to transfer heat from the fuel to the water. Boiler tube leakage can cause outages and huge power generation loss. Therefore, early detection of leaks in boiler tubes is necessary to avoid such ...
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MohammedAli Mudhsh and Rolla Almodfer
The traditional algorithms for recognizing handwritten alphanumeric characters are dependent on hand-designed features. In recent days, deep learning techniques have brought about new breakthrough technology for pattern recognition applications, especial...
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M. Altan Akdogan, Z. Pelin Bayindir, Cem Iyigun
Pág. 430 - 439
In this study, location analysis of emergency system vehicles is discussed using an approximate queueing model (AQM) on fully connected networks. We relax single vehicle restriction in each vehicle location which is commonly employed in the literature. O...
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