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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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Sara Rajaram and Cassie S. Mitchell
The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) into different modalities and data types is essential to improve Deep Learning (DL) for predictive medicine. This work presents DACMVA, a novel framework ...
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Wenkuan Huang, Hongbin Chen and Qiyang Zhao
The main research focus of this paper is to explore the use of the cycle-generative adversarial network (GAN) method to address the inter-turn fault issue in permanent magnet-synchronous motors (PMSMs). Specifically, this study aims to overcome the chall...
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Chenglin Yang, Dongliang Xu and Xiao Ma
Due to the increasing severity of network security issues, training corresponding detection models requires large datasets. In this work, we propose a novel method based on generative adversarial networks to synthesize network data traffic. We introduced...
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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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Dominic Lightbody, Duc-Minh Ngo, Andriy Temko, Colin C. Murphy and Emanuel Popovici
The growth of the Internet of Things (IoT) has led to a significant rise in cyber attacks and an expanded attack surface for the average consumer. In order to protect consumers and infrastructure, research into detecting malicious IoT activity must be of...
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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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Xiaofeng Liu, Liuqi Xiong, Yiming Zhang and Chenshuang Luo
Turbofan engines are known as the heart of the aircraft. The turbofan?s health state determines the aircraft?s operational status. Therefore, the equipment monitoring and maintenance of the engine is an important part of ensuring the healthy and stable o...
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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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