Showing 421 - 440 results of 4,968 for search 'data set detection', query time: 0.22s Refine Results
  1. 421
  2. 422

    Detection of Phantom Reads in Hyperledger Fabric by Luca Olivieri, Luca Negrini, Vincenzo Arceri, Badaruddin Chachar, Pietro Ferrara, Agostino Cortesi

    Published 2024-01-01
    “…In concurrent transactional systems, a phantom read occurs when a transaction retrieves a set of data, and simultaneously, new data is inserted, updated, or removed from that set by one or more other transactions, leading to unexpected data being read. …”
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  3. 423
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  5. 425

    An Automatic Method for Interest Point Detection by I. G. Zubov

    Published 2020-12-01
    “…The availability of digital cameras and large sets of annotated data, as well as the power of modern computing technologies, render monocular image analysis a dynamically developing direction in the field of machine vision. …”
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  6. 426

    Fish Detection Using Deep Learning by Suxia Cui, Yu Zhou, Yonghui Wang, Lujun Zhai

    Published 2020-01-01
    “…In this paper, a convolutional neural network (CNN) based fish detection method was proposed. The training data set was collected from the Gulf of Mexico by a digital camera. …”
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  7. 427

    Early Detection of Multiwavelength Blazar Variability by Hermann Stolte, Jonas Sinapius, Iftach Sadeh, Elisa Pueschel, Matthias Weidlich, David Berge

    Published 2025-01-01
    “…Based on unsupervised anomaly detection and clustering methods, we differentiate source variability from noisy background activity, without the need for a labeled training data set of flaring states. …”
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  8. 428

    Design of the DETECT project: automated cardiac arrest detection and activation of the emergency medical chain integrated into a wristband by Roos Edgar, Kambiz Ebrahimkheil, Niels T.B. Scholte, Catharina E. Jansen, Rypko J. Beukema, Marc A. Brouwer, Eelko Ronner, Aysun Cetinyurek-Yavuz, Marit van Barreveld, Marcel G.W. Dijkgraaf, Peter C. Stas, Eric Boersma, Niels van Royen, Judith L. Bonnes

    Published 2025-07-01
    “…To optimize cardiac arrest detection, DETECT-2 is set out to develop an algorithm for detection of sudden falls mimicking cardiac arrest-related collapses using accelerometry data (n = 20). …”
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  9. 429

    The OPS-SAT benchmark for detecting anomalies in satellite telemetry by Bogdan Ruszczak, Krzysztof Kotowski, David Evans, Jakub Nalepa

    Published 2025-04-01
    “…They were evaluated using the training-test dataset split introduced in this work, and we suggest a set of quality metrics which should be calculated to confront the new algorithms for anomaly detection while exploiting OPSSAT-AD. …”
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  10. 430

    Continual Semi-Supervised Malware Detection by Matthew Chin, Roberto Corizzo

    Published 2024-12-01
    “…Moreover, most of the research works proposed thus far adopt a fully supervised setting, which relies on fully labelled data and appears to be impractical in a rapidly evolving malware landscape. …”
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  11. 431

    Cloud Detection Challenge-Methods and Results by Alessio Barbaro Chisari, Luca Guarnera, Alessandro Ortis, Wladimiro Carlo Patatu, Bruno Casella, Luca Naso, Giuseppe Puglisi, Vincenzo del Zoppo, Mario Valerio Giuffrida, Sebastiano Battiato

    Published 2025-01-01
    “…This paper presents the Cloud Detection Challenge, an initiative aimed at enhancing cloud detection through innovative solutions using lidar-based ceilometer data. …”
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  12. 432

    Trajectory of Fifths in Tonal Mode Detection by Tomasz Lukaszewicz, Dariusz Kania

    Published 2025-01-01
    “…To assess the algorithm’s effectiveness, experiments were conducted using selected sets of Bach and Chopin works transposed into C major and A minor keys, as well as on pieces from the Saarland Music Data: MIDI-Audio Piano Music in their original keys. …”
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    Improving the Routing Security in Wireless Sensor Networks using Neutrosophic Set and Machine Learning Models by Hanadi Ahmad Simmak, Ahmed A El-Douh, Tareef S Alkellezli, Rabih Sbera, Darin shafek, Ahmed Abdelhafeez

    Published 2025-07-01
    “…Numerous methods have been put forth to identify and safeguard routing data because Wireless Sensor Networks (WSNs) are susceptible to attacks during data transfer. …”
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    Study on water quality analysis and early-warning technology based on rough set and evidence theory by ZHU Qiong-yao, ZHANG Guang-xin, FENG Tian-heng, HUANG Ping-jie, HOU Di-bo

    Published 2012-11-01
    “…Moreover, in order to solve the problem of redundancy parameters, the rough set was used. After these steps, a minimal data list was acquired. …”
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    Engineering geological settings of the Rječina River Valley (Croatia): a LiDAR-based approach by Petra Jagodnik, Sanja Bernat Gazibara

    Published 2025-12-01
    “…The Main Map was created by visually interpreting high-resolution LiDAR (Light Detection and Ranging) Digital Terrain Model (DTM), complemented by a review of pre-existing engineering geological data and field reconnaissance. …”
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  19. 439

    Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings. by Ioana Duta, Symon M Kariuki, Anthony K Ngugi, Angelina Kakooza Mwesige, Honorati Masanja, Daniel M Mwanga, Seth Owusu-Agyei, Ryan Wagner, J Helen Cross, Josemir W Sander, Charles R Newton, Arjune Sen, Gabriel Davis Jones

    Published 2025-02-01
    “…Here, we use a novel approach to assess the suitability and applicability of such clinical tools to aid screening and diagnosis of active convulsive epilepsy in settings beyond their original training contexts.<h4>Methods</h4>We sourced data from the Study of Epidemiology of Epilepsy in Demographic Sites dataset, which includes demographic information and clinical variables related to diagnosing epilepsy across five sub-Saharan African sites. …”
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  20. 440

    Multi-information fusion welding defect identification combining neighborhood rough set and optimized SVM by Zhiqiang FENG, Xianping ZENG, Naiwen FANG, Daidi ZHAO, Quan LI, Jiutian LUO, Xin LI

    Published 2025-05-01
    “…A multi-information fusion welding defect recognition method is proposed by combining NRS with optimized SVM to address the “big data” generated during the multi-sensor information fusion welding process. …”
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