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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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Seokjoon Kwon, Jae-Hyeon Park, Hee-Deok Jang, Hyunwoo Nam and Dong Eui Chang
Deep learning algorithms are widely used for pattern recognition in electronic noses, which are sensor arrays for gas mixtures. One of the challenges of using electronic noses is sensor drift, which can degrade the accuracy of the system over time, even ...
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Jiahui Zhao, Zhibin Li, Pan Liu, Mingye Zhang
Pág. 115 - 142
Demand prediction plays a critical role in traffic research. The key challenge of traffic demand prediction lies in modeling the complex spatial dependencies and temporal dynamics. However, there is no mature and widely accepted concept to support the so...
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Salman Ibne Eunus, Shahriar Hossain, A. E. M. Ridwan, Ashik Adnan, Md. Saiful Islam, Dewan Ziaul Karim, Golam Rabiul Alam and Jia Uddin
Accidents due to defective railway lines and derailments are common disasters that are observed frequently in Southeast Asian countries. It is imperative to run proper diagnosis over the detection of such faults to prevent such accidents. However, manual...
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Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias and Antonio G. Ravelo-García
This study presents a novel approach for kernel selection based on Kullback?Leibler divergence in variational autoencoders using features generated by the convolutional encoder. The proposed methodology focuses on identifying the most relevant subset of ...
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Lorenzo Arsini, Barbara Caccia, Andrea Ciardiello, Stefano Giagu and Carlo Mancini Terracciano
Graphs are versatile structures for the representation of many real-world data. Deep Learning on graphs is currently able to solve a wide range of problems with excellent results. However, both the generation of graphs and the handling of large graphs st...
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Karthikeyan Saminathan, Sai Tharun Reddy Mulka, Sangeetha Damodharan, Rajagopal Maheswar and Josip Lorincz
The COVID-19 pandemic made all organizations and enterprises work on cloud platforms from home, which greatly facilitates cyberattacks. Employees who work remotely and use cloud-based platforms are chosen as targets for cyberattacks. For that reason, cyb...
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Yang Shi, Zhenbo Wang, Tim J. LaClair, Chieh (Ross) Wang, Yunli Shao and Jinghui Yuan
The advent of connected vehicle (CV) technology offers new possibilities for a revolution in future transportation systems. With the availability of real-time traffic data from CVs, it is possible to more effectively optimize traffic signals to reduce co...
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Tala Talaei Khoei and Naima Kaabouch
Intrusion Detection Systems are expected to detect and prevent malicious activities in a network, such as a smart grid. However, they are the main systems targeted by cyber-attacks. A number of approaches have been proposed to classify and detect these a...
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Khaled A. Alaghbari, Heng-Siong Lim, Mohamad Hanif Md Saad and Yik Seng Yong
The intrusion detection system (IDS) is a promising technology for ensuring security against cyber-attacks in internet-of-things networks. In conventional IDS, anomaly detection and feature extraction are performed by two different models. In this paper,...
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