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Di Wang and Haizhong Qian
Existing research on automatic river network classification methods has difficulty scientifically quantifying and determining feature threshold settings and evaluating weights when calculating multi-indicator features of the local and overall structures ...
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Sufiyan Bashir Mukadam and Hemprasad Yashwant Patil
Skin cancer is one of the most fatal diseases for mankind. The early detection of skin cancer will facilitate its overall treatment and contribute towards lowering the mortalities. This paper presents the deep learning-based algorithm along with pre-proc...
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Hui Sheng, Min Liu, Jiyong Hu, Ping Li, Yali Peng and Yugen Yi
Time-series data is an appealing study topic in data mining and has a broad range of applications. Many approaches have been employed to handle time series classification (TSC) challenges with promising results, among which deep neural network methods ha...
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Yang Hu, Liangliang Gong, Xinyang Li, Hui Li, Ruoxin Zhang and Rentao Gu
When applying 5G network slicing technology, the operator?s network resources in the form of mutually isolated logical network slices provide specific service requirements and quality of service guarantees for smart grid communication services. In the fa...
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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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Madushi H. Pathmaperuma, Yogachandran Rahulamathavan, Safak Dogan and Ahmet Kondoz
In this study, a simple yet effective framework is proposed to characterize fine-grained in-app user activities performed on mobile applications using a convolutional neural network (CNN). The proposed framework uses a time window-based approach to split...
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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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Hanlin Sun, Wei Jie, Jonathan Loo, Liang Chen, Zhongmin Wang, Sugang Ma, Gang Li and Shuai Zhang
Presently, data that are collected from real systems and organized as information networks are universal. Mining hidden information from these data is generally helpful to understand and benefit the corresponding systems. The challenges of analyzing such...
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Lin-Huang Chang, Tsung-Han Lee, Hung-Chi Chu, Cheng-Wei Su
Pág. 216 - 229
The traffic classification based on the network applications is one important issue for network management. In this paper, we propose an application-based online and offline traffic classification, based on deep learning mechanisms, over software-defined...
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Ibrahim Ismael Alnaib,Omar Sh. Alyozbaky,Ali Abbawi
Pág. 6 - 16
Faults in the power system generally provide considerable changes in its quantities such as under or over-power, over-current, current or power direction, frequency, impedance, and power factor. Reading data related to both currents and voltages is usual...
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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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Kai Feng, Xitian Pi, Hongying Liu and Kai Sun
Myocardial infarction is one of the most threatening cardiovascular diseases for human beings. With the rapid development of wearable devices and portable electrocardiogram (ECG) medical devices, it is possible and conceivable to detect and monitor myoca...
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Zhonglin Ye, Haixing Zhao, Ke Zhang and Yu Zhu
Network representation learning is a key research field in network data mining. In this paper, we propose a novel multi-view network representation algorithm (MVNR), which embeds multi-scale relations of network vertices into the low dimensional represen...
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Torrey Wagner, Dennis Guhl and Brent Langhals
Given the emergence of China as a political and economic power in the 21st century, there is increased interest in analyzing Chinese news articles to better understand developing trends in China. Because of the volume of the material, automating the cate...
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Chenhong Yan, Shefeng Yan, Tianyi Yao, Yang Yu, Guang Pan, Lu Liu, Mou Wang and Jisheng Bai
Ship-radiated noise classification is critical in ocean acoustics. Recently, the feature extraction method combined with time?frequency spectrograms and convolutional neural networks (CNNs) has effectively described the differences between various underw...
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María Gema Carrasco-García, María Inmaculada Rodríguez-García, Juan Jesús Ruíz-Aguilar, Lipika Deka, David Elizondo and Ignacio José Turias Domínguez
Hyperspectral technology has been playing a leading role in monitoring oil spills in marine environments, which is an issue of international concern. In the case of monitoring oil spills in local areas, hyperspectral technology of small dimensions is the...
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Tatyana Aksenovich and Vasiliy Selivanov
During geomagnetic storms, which are a result of solar wind?s interaction with the Earth?s magnetosphere, geomagnetically induced currents (GICs) begin to flow in the long, high-voltage electrical networks on the Earth?s surface. It causes a number of ne...
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JongBae Kim
This technology can prevent accidents involving large vehicles, such as trucks or buses, by selecting an optimal driving lane for safe autonomous driving. This paper proposes a method for detecting forward-driving vehicles within road images obtained fro...
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Jee-Tae Park, Chang-Yui Shin, Ui-Jun Baek and Myung-Sup Kim
The classification of encrypted traffic plays a crucial role in network management and security. As encrypted network traffic becomes increasingly complicated and challenging to analyze, there is a growing need for more efficient and comprehensive analyt...
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Hangfei He, Junyang Chen, Hongkun Chen, Borui Zeng, Yutong Huang, Yudan Zhaopeng and Xiaoyan Chen
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