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Markus Baumann, Christian Koch and Stephan Staudacher
Model-based predictive maintenance using high-frequency in-flight data requires digital twins that can model the dynamics of their physical twin with high precision. The models of the twins need to be fast and dynamically updatable. Machine learning offe...
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Rito Clifford Maswanganyi, Chungling Tu, Pius Adewale Owolawi and Shengzhi Du
Transfer learning (TL) has been proven to be one of the most significant techniques for cross-subject classification in electroencephalogram (EEG)-based brain-computer interfaces (BCI). Hence, it is widely used to address the challenges of cross-session ...
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Nicola Landro, Ignazio Gallo and Riccardo La Grassa
Nowadays, the transfer learning technique can be successfully applied in the deep learning field through techniques that fine-tune the CNN?s starting point so it may learn over a huge dataset such as ImageNet and continue to learn on a fixed dataset to a...
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Alper Taner, Mahtem Teweldemedhin Mengstu, Kemal Çagatay Selvi, Hüseyin Duran, Ibrahim Gür and Nicoleta Ungureanu
Having the advantages of speed, suitability and high accuracy, computer vision has been effectively utilized as a non-destructive approach to automatically recognize and classify fruits and vegetables, to meet the increased demand for food quality-sensin...
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David Naseh, Mahdi Abdollahpour and Daniele Tarchi
This paper explores the practical implementation and performance analysis of distributed learning (DL) frameworks on various client platforms, responding to the dynamic landscape of 6G technology and the pressing need for a fully connected distributed in...
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Jingwen Yang and Ruohua Zhou
Whisper speaker recognition (WSR) has received extensive attention from researchers in recent years, and it plays an important role in medical, judicial, and other fields. Among them, the establishment of a whisper dataset is very important for the study...
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Wandile Nhlapho, Marcellin Atemkeng, Yusuf Brima and Jean-Claude Ndogmo
The advent of deep learning (DL) has revolutionized medical imaging, offering unprecedented avenues for accurate disease classification and diagnosis. DL models have shown remarkable promise for classifying brain tumors from Magnetic Resonance Imaging (M...
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Zhe Yin, Mingkang Peng, Zhaodong Guo, Yue Zhao, Yaoyu Li, Wuping Zhang, Fuzhong Li and Xiaohong Guo
With the advancement of machine vision technology, pig face recognition has garnered significant attention as a key component in the establishment of precision breeding models. In order to explore non-contact individual pig recognition, this study propos...
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Peranut Nimitsurachat and Peter Washington
Emotion recognition models using audio input data can enable the development of interactive systems with applications in mental healthcare, marketing, gaming, and social media analysis. While the field of affective computing using audio data is rich, a m...
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Yunfei Yang, Zhicheng Zhang, Jiapeng Zhao, Bin Zhang, Lei Zhang, Qi Hu and Jianglong Sun
Resistance serves as a critical performance metric for ships. Swift and accurate resistance prediction can enhance ship design efficiency. Currently, methods for determining ship resistance encompass model tests, estimation techniques, and computational ...
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Jiwun Yoon, Sang-Yong Lee and Ji-Yong Lee
Humans share a similar body structure, but each individual possesses unique characteristics, which we define as one?s body type. Various classification methods have been devised to understand and assess these body types. Recent research has applied artif...
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Nan Lao Ywet, Aye Aye Maw, Tuan Anh Nguyen and Jae-Woo Lee
Urban Air Mobility (UAM) emerges as a transformative approach to address urban congestion and pollution, offering efficient and sustainable transportation for people and goods. Central to UAM is the Operational Digital Twin (ODT), which plays a crucial r...
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Shihao Ma, Jiao Wu, Zhijun Zhang and Yala Tong
Addressing the limitations, including low automation, slow recognition speed, and limited universality, of current mudslide disaster detection techniques in remote sensing imagery, this study employs deep learning methods for enhanced mudslide disaster d...
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Daniel Rocha, Filomena Soares, Eva Oliveira and Vítor Carvalho
The ways in which people dress, as well as the styles that they prefer for different contexts and occasions, are part of their identity. Every day, blind people face limitations in identifying and inspecting their garments, and dressing can be a difficul...
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Mostafa Hamdy Salem, Yujian Li, Zhaoying Liu and Ahmed M. AbdelTawab
Deep learning has been used to improve intelligent transportation systems (ITS) by classifying ship targets in interior waterways. Researchers have created numerous classification methods, but they have low accuracy and misclassify other ship targets. As...
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Ugne Orinaite, Vilte Karaliute, Mayur Pal and Minvydas Ragulskis
This paper presents the development of an underwater crack detection system for structural integrity assessment of submerged structures, such as offshore oil and gas installations, underwater pipelines, underwater foundations for bridges, dams, etc. Our ...
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Muhammad Akhtar, Iqbal Murtza, Muhammad Adnan and Ayesha Saadia
Natural scene classification, which has potential applications in precision agriculture, environmental monitoring, and disaster management, poses significant challenges due to variations in the spatial resolution, spectral resolution, texture, and size o...
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Yejin Lee, Suho Lee and Sangheum Hwang
Fine-grained image recognition aims to classify fine subcategories belonging to the same parent category, such as vehicle model or bird species classification. This is an inherently challenging task because a classifier must capture subtle interclass dif...
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Gang Wang, Dong Liu, Chunrui Zhang and Teng Hu
This work has potential usages in cyber-attack detection in air-gapped internal networks that lack sufficient labeled data samples to build detection models for network attack activities.
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Xiaotong Cui, Hongxin Zhang, Xing Fang, Yuanzhen Wang, Danzhi Wang, Fan Fan and Lei Shu
The leakage signals, including electromagnetic, energy, time, and temperature, generated during the operation of password devices contain highly correlated key information, which leads to security vulnerabilities. In traditional encryption algorithms, th...
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