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Yeong-Hyeon Byeon and Keun-Chang Kwak
When acquiring electrocardiogram (ECG) signals, the placement of electrode patches is crucial for acquiring electrocardiographic signals. Constant displacement positions are essential for ensuring the consistency of the ECG signal when used for individua...
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Feixiang Ren, Jiwang Du and Daofang Chang
To address the challenge of accurate lifespan prediction for bearings in different operating conditions within ship propulsion shaft systems, a two-stage prediction model based on an enhanced domain adversarial neural network (DANN) is proposed. Firstly,...
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Rokaya Eltehewy, Ahmed Abouelfarag and Sherine Nagy Saleh
Rapid damage identification and classification in disastrous situations and natural disasters are crucial for efficiently directing aid and resources. With the development of deep learning techniques and the availability of imagery content on social medi...
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Jianzhuo Yan, Lihong Chen, Yongchuan Yu, Hongxia Xu, Qingcai Gao, Kunpeng Cao and Jianhui Chen
With the rapid development of the internet and social media, extracting emergency events from online news reports has become an urgent need for public safety. However, current studies on the text mining of emergency information mainly focus on text class...
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Rina Komatsu and Tad Gonsalves
In CycleGAN, an image-to-image translation architecture was established without the use of paired datasets by employing both adversarial and cycle consistency loss. The success of CycleGAN was followed by numerous studies that proposed new translation mo...
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Shunlei Li, Muhammad Adeel Azam, Ajay Gunalan and Leonardo S. Mattos
Optical coherence tomography (OCT) is a rapidly evolving imaging technology that combines a broadband and low-coherence light source with interferometry and signal processing to produce high-resolution images of living tissues. However, the speckle noise...
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Liquan Zhao and Yan Liu
The transfer learning method is used to extend our existing model to more difficult scenarios, thereby accelerating the training process and improving learning performance. The conditional adversarial domain adaptation method proposed in 2018 is a partic...
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Nikolay Kalashnikov,Olexandr Kokhanov,Olexandr Iakovenko,Nataliia Kushnirenko
Pág. 37 - 42
This paper addresses the task of developing a steganographic method to hide information, resistant to analysis based on the Rich model (which includes several different submodels), using statistical indicators for the distribution of the pairs of coeffic...
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Daniel S. Berman, Anna L. Buczak, Jeffrey S. Chavis and Cherita L. Corbett
This survey paper describes a literature review of deep learning (DL) methods for cyber security applications. A short tutorial-style description of each DL method is provided, including deep autoencoders, restricted Boltzmann machines, recurrent neural ...
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