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Jianhe Li and Suohai Fan
In recent years, graph neural networks (GNNs) have played an important role in graph representation learning and have successfully achieved excellent results in semi-supervised classification. However, these GNNs often neglect the global smoothing of the...
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Juan M. Lujano-Rojas, Rodolfo Dufo-López, Jesús Sergio Artal-Sevil and Eduardo García-Paricio
Assessing the training process of artificial neural networks (ANNs) is vital for enhancing their performance and broadening their applicability. This paper employs the Monte Carlo simulation (MCS) technique, integrated with a stopping criterion, to const...
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Yiwen Wang, Dongna Liu, Haiyu Dong, Junwei Lin, Qi Zhang and Xiaohui Zhang
Through the stability evaluation of a slope, a landslide geological disaster can be identified, and the safety and risk control of a project can be ensured. This work proposes an improved sparrow search algorithm to optimize the slope safety factor predi...
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Javad Hassannataj Joloudari, Abdolreza Marefat, Mohammad Ali Nematollahi, Solomon Sunday Oyelere and Sadiq Hussain
Imbalanced Data (ID) is a problem that deters Machine Learning (ML) models from achieving satisfactory results. ID is the occurrence of a situation where the quantity of the samples belonging to one class outnumbers that of the other by a wide margin, ma...
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Qi Yan, Zhiqiang Wan and Chao Yang
Flight load calculation, an important step in aircraft design and optimization, typically involves millions of computations and requires significant computing resources and time. Improving the efficiency of flight load calculations while maintaining accu...
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Ayanabha Jana and Shridevi S. Krishnakumar
The proposed research deals with constructing a sign gesture recognition system to enable improved interaction between sign and non-sign users. With respect to this goal, five types of features are utilized?hand coordinates, convolutional features, convo...
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SK Safdar Hossain, Bamidele Victor Ayodele, Zaid Abdulhamid Alhulaybi and Muhammad Mudassir Ahmad Alwi
This study explored the feasibility of various multilayer perceptron configurations for modeling biohydrogen production from biodiesel production waste. Based on the best model, knowledge of how various parameters influence biohydrogen production can be ...
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Saurabh Agarwal and Ki-Hyun Jung
Digital images are very popular and commonly used for hiding crucial data. In a few instances, image steganography is misused for communicating with improper data. In this paper, a robust deep neural network is proposed for the identification of content-...
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Zhao Zhang, Feng Feng and Tingting Huang
The size of datasets is growing exponentially as information technology advances, and it is becoming more and more crucial to provide efficient learning algorithms for neural networks to handle massive amounts of data. Due to their potential for handling...
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Huynh Cong Viet Ngu and Keon Myung Lee
Due to energy efficiency, spiking neural networks (SNNs) have gradually been considered as an alternative to convolutional neural networks (CNNs) in various machine learning tasks. In image recognition tasks, leveraging the superior capability of CNNs, t...
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Anna Kurtukova, Aleksandr Romanov, Alexander Shelupanov and Anastasia Fedotova
This paper is a continuation of our previous work on solving source code authorship identification problems. The analysis of heterogeneous source code is a relevant issue for copyright protection in commercial software development. This is related to the...
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Fekhr Eddine Keddous and Amir Nakib
Convolutional neural networks (CNNs) have powerful representation learning capabilities by automatically learning and extracting features directly from inputs. In classification applications, CNN models are typically composed of: convolutional layers, po...
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Peng-Fei Xu, Chen-Bo Han, Hong-Xia Cheng, Chen Cheng and Tong Ge
A three-degrees-of-freedom model, including surge, sway and yaw motion, with differential thrusters is proposed to describe unmanned surface vehicle (USV) dynamics in this study. The experiment is carried out in the Qing Huai River and the data obtained ...
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Youngmin Park, Euihyun Kim, Youngjin Choi, Gwangho Seo, Youngtaeg Kim and Hokyun Kim
Typhoon attacks on the Korean Peninsula have recently become more frequent, and the strength of these typhoons is also gradually increasing because of climate change. Typhoon attacks cause storm surges in coastal regions; therefore, forecasts that enable...
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Yonggang Wang, Ruimin Xiao, Yizhi Yin and Tan Liu
Yield prediction for tomatoes in greenhouses is an important basis for making production plans, and yield prediction accuracy directly affects economic benefits. To improve the prediction accuracy of tomato yield in Chinese-style solar greenhouses (CSGs)...
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Wenting Liu, Li Zhou and Jie Chen
Face recognition algorithms based on deep learning methods have become increasingly popular. Most of these are based on highly precise but complex convolutional neural networks (CNNs), which require significant computing resources and storage, and are di...
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Sunghwan Moon
Deep neural networks have shown very successful performance in a wide range of tasks, but a theory of why they work so well is in the early stage. Recently, the expressive power of neural networks, important for understanding deep learning, has received ...
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Akm Ashiquzzaman, Hyunmin Lee, Kwangki Kim, Hye-Young Kim, Jaehyung Park and Jinsul Kim
Current deep learning convolutional neural network (DCNN) -based hand gesture detectors with acute precision demand incredibly high-performance computing power. Although DCNN-based detectors are capable of accurate classification, the sheer computing pow...
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Kun Fan, Chungin Joung and Seungjun Baek
Video prediction which maps a sequence of past video frames into realistic future video frames is a challenging task because it is difficult to generate realistic frames and model the coherent relationship between consecutive video frames. In this paper,...
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Sandeli Priyanwada Kasthuri Arachchi, Timothy K. Shih and Noorkholis Luthfil Hakim
Video classification is an essential process for analyzing the pervasive semantic information of video content in computer vision. Traditional hand-crafted features are insufficient when classifying complex video information due to the similarity of visu...
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