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Ali Raza, Mohammad Rustom Al Nasar, Essam Said Hanandeh, Raed Abu Zitar et al. • Technologies
(2023)
Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily li...
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Open Access (DOAJ)
DOI: 10.3390/technologies11020055
Ya Zhang, Ravie Chandren Muniyandi, Faizan Qamar • Applied Sciences
(2025)
In the rapid development of the Internet of Things (IoT) and large-scale distributed networks, Intrusion Detection Systems (IDS) face significant challenges in handling complex spatiotemporal features and addressing data imbalance issues. T...
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Open Access (DOAJ)
DOI: 10.3390/app15031552
Xiaoxiao Ma, Jia Xin Wu, Shan Xue, Jian Yu Yang et al. • IEEE Transactions on Knowledge and Data Engineering
(2021)
Anomalies are rare observations (e.g., data records or events) that deviate significantly from the others in the sample. Over the past few decades, research on anomaly mining has received increasing interests due to the implications of thes...
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Open Access
DOI: https://doi.org/10.1109/tkde.2021.3118815
Siwei Yu, Jianwei Ma • Reviews of Geophysics
(2021)
Abstract Recently deep learning (DL), as a new data‐driven technique compared to conventional approaches, has attracted increasing attention in geophysical community, resulting in many opportunities and challenges. DL was proven to have the...
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DOI: https://doi.org/10.1029/2021rg000742
Zhiqiang Zhang, Yi Chen Zhao, Xiangke Liao, Wenqiang Shi et al. • Briefings in Functional Genomics
(2018)
Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fo...
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DOI: https://doi.org/10.1093/bfgp/ely030
Vera Rimmer, Davy Preuveneers, Marc Juarez, Tom Van Goethem et al. • Network and Distributed System Security Symposium
(2018)
Several studies have shown that the network traffic that is generated by a visit to a website over Tor reveals information specific to the website through the timing and sizes of network packets.By capturing traffic traces between users and...
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Open Access
DOI: https://doi.org/10.14722/ndss.2018.23105
Roberto De Fazio, Matteo Paiano, Ramiro Velazquez, Carolina Del-Valle-Soto et al. • Applied Sciences
(2026)
Automatic sleep staging is fundamental for diagnosing sleep disorders and enabling long-term sleep monitoring with wearable devices. Although Deep Learning has significantly improved classification performance, balancing accuracy with compu...
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Open Access (DOAJ)
DOI: 10.3390/app16168164
Bang Zhu, Wenkai Cheng, Shiting Wen, Yuran Ma et al. • Scientific Reports
(2025)
Abstract The application of the $$\Phi$$ -OTDR (Phase-Optical Time Domain Reflectometry) system in real-time monitoring of power grid infrastructure has been proven effective in identifying and classifying various anomalies, such as digging...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-29691-y
Jin Mo Ahn, Sangsoo Kim, Kwang-Sung Ahn, Sung-Hoon Cho et al. • BMC Ophthalmology
(2019)
Abstract Background This study is to evaluate the accuracy of machine learning for differentiation between optic neuropathies, pseudopapilledema (PPE) and normals. Methods Two hundred and ninety-five images of optic neuropathies, 295 images...
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Open Access (DOAJ)
DOI: 10.1186/s12886-019-1184-0
salma mostafa ahmed helmy, Salsabil Amin, Abeer mahmoud, El-Sayed El-Horabty • International Journal of Intelligent Computing and Information Sciences
(2026)
The healthcare sector is undergoing rapid transformation driven by advances in artificial intelligence and machine learning, with quantum computing emerging as the next major breakthrough. This paper presents a comparative analysis of class...
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Open Access (DOAJ)
DOI: 10.21608/ijicis.2026.442636.1439
Shiqi Feng, Xuquan Wang, Xiong Dun, Zhanshan Wang et al. • IEEE Photonics Journal
(2025)
Encoded computational hyperspectral cameras, propelled by advances in compressed sensing theory, making both miniaturization and real-time hyperspectral imaging feasible. Spectral-encoded or spatial-encoded hyperspectral imaging strategy ha...
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Open Access (DOAJ)
DOI: 10.1109/JPHOT.2025.3624799
Kirill Djebko, Patrick Schurk, Tom Baumann, Frank Puppe et al. • Aerospace
(2025)
Artificial Intelligence (AI) is rapidly transforming engineering fields, from robotics to aerospace, with applications in control systems for UAVs and satellites. This work builds on a previously developed AI attitude controller for the Inn...
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Open Access (DOAJ)
DOI: 10.3390/aerospace12121039
Kalab Yigermal Gete, Asnakew Achaw Ayele • BMC Neurology
(2025)
Abstract Background Non-contrast CT (NCCT) is first-line imaging for suspected acute ischemic stroke (AIS) but has limited early sensitivity; deep learning (DL) may improve patient-level detection. Objectives To estimate the diagnostic accu...
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Open Access (DOAJ)
DOI: 10.1186/s12883-025-04528-3
Ghenwa Chamouni, Filippo Lococo, Carolina Sassorossi, Nkunzi Atuhaire et al. • Frontiers in Public Health
(2025)
IntroductionArtificial intelligence (AI) is increasingly integrating into the healthcare field, particularly in lung cancer care, including screening, diagnosis, treatment, and prognosis. While these applications offer promising advancement...
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Open Access (DOAJ)
DOI: 10.3389/fpubh.2025.1663298
Ahmad Y. Javaid, Quamar Niyaz, Weiqing Sun, Mansoor Alam • International Conference on Bio-Inspired Models of Network, Information and Computing Systems (BIONETICS)
(2016)
A Network Intrusion Detection System (NIDS) helps system administrators to detect network security breaches in their organizations. However, many challenges arise while developing a flexible and efficient NIDS for unforeseen and unpredictab...
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DOI: https://doi.org/10.4108/eai.3-12-2015.2262516
Haohan Wang, Bhiksha Raj • arXiv (Cornell University)
(2017)
This paper is a review of the evolutionary history of deep learning models. It covers from the genesis of neural networks when associationism modeling of the brain is studied, to the models that dominate the last decade of research in deep ...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1702.07800
Asmaa Hani Halbouni, Teddy Surya Gunawan, Mohamed Hadi Habaebi, Murad Halbouni et al. • IEEE Access
(2022)
The rapid evolution and growth of the internet through the last decades led to more concern about cyber-attacks that are continuously increasing and changing. As a result, an effective intrusion detection system was required to protect data...
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DOI: https://doi.org/10.1109/access.2022.3151248
Bethany Lusch, J. Nathan Kutz, Steven L. Brunton • Nature Communications
(2018)
Identifying coordinate transformations that make strongly nonlinear dynamics approximately linear has the potential to enable nonlinear prediction, estimation, and control using linear theory. The Koopman operator is a leading data-driven e...
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DOI: https://doi.org/10.1038/s41467-018-07210-0
PMC: 6251871
François Chollet, JJ Allaire (2018)
Introduces deep learning systems using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples...
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Asma Cherif, Arwa Badhib, Heyfa Ammar, Suhair Alshehri et al. • Journal of King Saud University: Computer and Information Sciences
(2023)
Credit card fraud is becoming a serious and growing problem as a result of the emergence of innovative technologies and communication methods, such as contactless payment. In this article, we present an in-depth review of cutting-edge resea...
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Open Access (DOAJ)
DOI: 10.1016/j.jksuci.2022.11.008