A wireless reader for detecting frequency shift of passive sensors by Fariborz Mirlou, Emine Bardakci, Taher Abbasiasl, Levent Beker

“…While passive disposable, chip-free, and batteryless sensors have been widely studied, benchtop equipment is still required for data collection, limiting usage to laboratory settings. …”
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Edge AI for Real-Time Anomaly Detection in Smart Homes by Manuel J. C. S. Reis, Carlos Serôdio

“…Future work will investigate self-supervised learning, transformer-based detection, and deployment in real-world operational settings.…”
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HPD-Kit: a comprehensive toolkit for pathogen detection and analysis by Tengcheng Que, Tengcheng Que, Tengcheng Que, Wen Li, Wen Li, Wen Li, Zhining Zhang, Yunlin He, Kangming He, Hong Qiu, Hong Qiu, Juan Huang, Zhiwei Lu, Chunlan Jiang, Yongjian Huang, Hui Huang, Qiuyu Wu, Panyu Chen, Yanling Hu, Yanling Hu, Yanling Hu, Wenjian Liu

“…The toolkit provides both open-source software and a web interface for streamlined one-click analysis.ResultsValidation with simulated data showed HPD-Kit maintains high detection accuracy even at low pathogen abundance. …”
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Long-Range Wide Area Network Intrusion Detection at the Edge by Gonçalo Esteves, Filipe Fidalgo, Nuno Cruz, José Simão

“…The current work uses third-party multi-vendor sensor data obtained in the city of Lisbon for training and validating the models. …”
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Anomaly Detection for MVB Network Based on Logistic Ensemble Learning by Huizhen WANG, Lide WANG, Yueyi YANG, Ping SHEN

“…Based on the analysis of common faults in MVB network, with extracting the network state features from the MVB physical layer and data link layer, an detection method based on heterogeneous Logistic ensemble learning to detect MVB network anomaly and avoid breakdown maintenance to the maximum extent was proposed. …”
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Early Detection of Parkinson's Disease: Ensemble Learning for Improved Diagnosis by Raut Komal, Balpande Vijaya

“…This research highlights the potential of these advanced techniques in clinical settings.…”
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Improved spectral clustering algorithm and its application in MCI detection by Jie XIANG, Dong-qin ZHAO

“…In order to detect mild cognitive impairment (MCI) using functional magnetic resonance imaging (fMRI)，a method based on fMRI clustering was proposed fMRI data were clustered to obtain the blood oxygen level dependence( BOLD) change model of MCI patients，then abnormal patterns were used to detect disease.The traditional spectral clustering algorithm needs to calculate all of the eigenvalue and eigenvector，so time and space complexity is higher.An improved spectral clustering method was proposed which modified the similar matrix construction method and the setting method of σ and k，and then this method was applied to clustering and detection of MCI patients.To verify the performance of the proposed method，the comparison of the clustering result，classification accuracy using traditional algorithm and Nyström is also done.The comparative experimental results show that the proposed method can get BOLD pattern more accurately，the accuracy of MCI detection is higher than the other two algorithms，and the time and space complexity are less than the traditional algorithm.…”
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Improved spectral clustering algorithm and its application in MCI detection by Jie XIANG, Dong-qin ZHAO

“…In order to detect mild cognitive impairment (MCI) using functional magnetic resonance imaging (fMRI)，a method based on fMRI clustering was proposed fMRI data were clustered to obtain the blood oxygen level dependence( BOLD) change model of MCI patients，then abnormal patterns were used to detect disease.The traditional spectral clustering algorithm needs to calculate all of the eigenvalue and eigenvector，so time and space complexity is higher.An improved spectral clustering method was proposed which modified the similar matrix construction method and the setting method of σ and k，and then this method was applied to clustering and detection of MCI patients.To verify the performance of the proposed method，the comparison of the clustering result，classification accuracy using traditional algorithm and Nyström is also done.The comparative experimental results show that the proposed method can get BOLD pattern more accurately，the accuracy of MCI detection is higher than the other two algorithms，and the time and space complexity are less than the traditional algorithm.…”
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Detecting emotional disorder with eye movement features in sports watching by Wei Qiang, Wei Qiang, Lin Yang, Xucheng Zhang, Na Liu, Yanyong Wang, Jipeng Zhang, Yixin Long, Weiwei Xu, Wei Sun

“…IntroductionDigital technologies have significantly advanced the detection of emotional disorders (EmD) in clinical settings. …”
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SIFT Feature-Based Video Camera Boundary Detection Algorithm by Lingqiang Kong

“…The algorithm can detect sudden changes/gradual changes of the lens at the same time without setting a threshold. …”
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A deep learning-based approach for the detection of cucumber diseases. by Lars Raufer, Jasper Wiedey, Malte Mueller, Pascal Penava, Ricardo Buettner

“…This result sets a new benchmark within the dataset, highlighting the potential of deep learning techniques in agricultural disease detection. …”
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Sudden Fall Detection of Human Body Using Transformer Model by Duncan Kibet, Min Seop So, Hahyeon Kang, Yongsu Han, Jong-Ho Shin

“…This approach has practical applications in settings like elderly care facilities and home monitoring systems, where reliable fall detection can support faster intervention. …”
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Transfer learning methods for Three-Axis CNC anomaly detection by Eugene Li, Yang Li, Sasank Kakarla, William Melek, Sanjeev Bedi

“…Before transfer learning can be applied, the Maximum Mean Discrepancy (MMD) score between the source and target data sets should be evaluated. A low MMD score indicates that the system can be transferred, but it is unclear what the physical implication of this score is. …”
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An Iterative Information-Theoretic Approach to the Detection of Structures in Complex Systems by Marco Villani, Laura Sani, Riccardo Pecori, Michele Amoretti, Andrea Roli, Monica Mordonini, Roberto Serra, Stefano Cagnoni

“…The method iterates two basic steps: detection of relevant variable sets based on the computation of the Relevance Index, and application of a sieving algorithm, which refines the results. …”
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Deep learning algorithms for detecting fractured instruments in root canals by Ekin Deniz Çatmabacak, İrem Çetinkaya

“…Methods A dataset of 700 annotated PAs, including 381 teeth with FEIs, was divided into training, validation, and test sets (60/20/20 split). Five DL models—DenseNet201, EfficientNet B0, ResNet-18, VGG-19, and MaxVit-T—were trained using transfer learning and data augmentation techniques. …”
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Detecting Software Anomalies in Robots by Means of One-class Classifiers by Héctor Quintián, Esteban Jove, Francisco Zayas-Gato, Nuño Basurto, Carlos Cambra, Álvaro Herrero

“…While most anomaly detection research has focused on hardware anomalies, this study addresses the underexplored challenge of software anomaly detection in component-based robotic systems. …”
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Detection and Classification of Sporadic E Using Convolutional Neural Networks by J. A. Ellis, D. J. Emmons, M. B. Cohen

“…After corresponding the two data sets, a total of 36,521 samples are available for training and testing the models. …”
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Automated detection of hospital outbreaks: A systematic review of methods. by Brice Leclère, David L Buckeridge, Pierre-Yves Boëlle, Pascal Astagneau, Didier Lepelletier

“…<h4>Results</h4>Twenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). …”
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Cost-effectiveness of household contact investigation for detection of tuberculosis in Pakistan by Hamidah Hussain, Bjarne Robberstad, Thorkild Tylleskär, Jacob Creswell, Amyn Malik, Junaid F Ahmed, Sara Siddiqui, Farhana Amanullah

“…Objectives Despite WHO guidelines recommending household contact investigation, and studies showing the impact of active screening, most tuberculosis (TB) programmes in resource-limited settings only carry out passive contact investigation. …”
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Transformer-based ECG classification for early detection of cardiac arrhythmias by Sunnia Ikram, Amna Ikram, Harvinder Singh, Malik Daler Ali Awan, Sajid Naveed, Isabel De la Torre Díez, Henry Fabian Gongora, Thania Candelaria Chio Montero

“…Electrocardiogram (ECG) classification plays a critical role in early detection and trocardiogram (ECG) classification plays a critical role in early detection and monitoring cardiovascular diseases. …”
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