Výsledky vyhledávání - "supervised algorithm"

  1. 1

    A self‐supervised strategy for fully automatic segmentation of renal dynamic contrast‐enhanced magnetic resonance images Autor Huang, Wenjian, Li, Hao, Wang, Rui, Zhang, Xiaodong, Wang, Xiaoying, Zhang, Jue

    ISSN: 0094-2405, 2473-4209, 2473-4209
    Vydáno: United States 01.10.2019
    Vydáno v Medical physics (Lancaster) (01.10.2019)
    “…Purpose An automated accurate segmentation for dynamic contrast‐enhanced magnetic resonance (DCE‐MR) image sequences is essential for quantification of renal…”
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  2. 2

    A Survey on Automated Sentimental Analysis of Twitter Data using Supervised Algorithm Autor Mr. V. Chandra Sekhar Reddy, K. Manvith Reddy, CH. Vachan Sai, K. Suraj, A. Abhinash

    ISSN: 2581-9429, 2581-9429
    Vydáno: 09.11.2022
    “…Now a days as most of the people express their opinions and views on a particular topic, product or any other subject via social media, identifying the sentiment behind the statement has gained much significance…”
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  3. 3

    Semi-Supervised Learning for Low-cost Personalized Obstructive Sleep Apnea Detection Using Unsupervised Deep Learning and Single-Lead Electrocardiogram Autor Hu, Shuaicong, Wang, Ya'nan, Liu, Jian, Yang, Cuiwei, Wang, Aiguo, Li, Kuanzheng, Liu, Wenxin

    ISSN: 2168-2194, 2168-2208, 2168-2208
    Vydáno: United States IEEE 01.11.2023
    “…)-based OSA detection, by proposing an automatic semi-supervised algorithm for automated low-cost personalization fine-tuning. Methods…”
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  4. 4

    Neurodevelopmental predictors of treatment response in schizophrenia and bipolar disorder Autor Iftimovici, Anton, Krebs, Emma, Dalfin, William, Legrand, Adrien, Scoriels, Linda, Martinez, Gilles, Bendjemaa, Narjes, Duchesnay, Edouard, Chaumette, Boris, Krebs, Marie-Odile

    ISSN: 0033-2917, 1469-8978, 1469-8978
    Vydáno: England Cambridge University Press 01.10.2024
    Vydáno v Psychological medicine (01.10.2024)
    “… A supervised algorithm leveraged NSS and age at first clinical signs to classify between resistance and response in schizophrenia…”
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  5. 5

    Translational Algorithms for Technological Dietary Quality Assessment Integrating Nutrimetabolic Data with Machine Learning Methods Autor de la O, Víctor, Fernández-Cruz, Edwin, Matía Matin, Pilar, Larrad-Sainz, Angélica, Espadas Gil, José Luis, Barabash, Ana, Fernández-Díaz, Cristina M., Calle-Pascual, Alfonso L., Rubio-Herrera, Miguel A., Martínez, J. Alfredo

    ISSN: 2072-6643, 2072-6643
    Vydáno: Switzerland MDPI AG 07.11.2024
    Vydáno v Nutrients (07.11.2024)
    “…: We analyzed data from 138 subjects from the European Dietary Deal project through comprehensive examinations, lifestyle questionnaires, and fasting blood samples…”
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  6. 6

    A functional source separation algorithm to enhance error-related potentials monitoring in noninvasive brain-computer interface Autor Ferracuti, Francesco, Casadei, Valentina, Marcantoni, Ilaria, Iarlori, Sabrina, Burattini, Laura, Monteriù, Andrea, Porcaro, Camillo

    ISSN: 0169-2607, 1872-7565, 1872-7565
    Vydáno: Ireland Elsevier B.V 01.07.2020
    “…•Semi Blind functional source separation (FSS) identify optimal spatial filter for BCI.•FSS algorithm is able to enhance error-related potential (ErrPs)…”
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  7. 7

    SGM: a novel time-frequency algorithm based on unsupervised learning improves high-frequency oscillation detection in epilepsy Autor Migliorelli, Carolina, Bachiller, Alejandro, Alonso, Joan F, Romero, Sergio, Aparicio, Javier, Jacobs-Le Van, Julia, Mañanas, Miguel A, San Antonio-Arce, Victoria

    ISSN: 1741-2560, 1741-2552, 1741-2552
    Vydáno: England IOP Publishing 22.04.2020
    Vydáno v Journal of neural engineering (22.04.2020)
    “… This algorithm does not depend on parameter tuning on a subject (or database) basis, uses time-frequency characteristics, and relies on non-supervised classification to determine if the events standing out from the baseline activity are HFO…”
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  8. 8

    Transfer Kernel Common Spatial Patterns for Motor Imagery Brain-Computer Interface Classification Autor Zhang, Pengju, Liu, Shucong, Zheng, Dezhi, Dai, Mengxi

    ISSN: 1748-670X, 1748-6718, 1748-6718
    Vydáno: Cairo, Egypt Hindawi Publishing Corporation 01.01.2018
    “…) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model…”
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  9. 9

    The Effect of Personalization on Smartphone-Based Fall Detectors Autor Medrano, Carlos, Plaza, Inmaculada, Igual, Raúl, Sánchez, Ángel, Castro, Manuel

    ISSN: 1424-8220, 1424-8220
    Vydáno: Switzerland MDPI 18.01.2016
    Vydáno v Sensors (Basel, Switzerland) (18.01.2016)
    “…—Nearest Neighbor (NN), Local Outlier Factor (LOF) and One-Class Support Vector Machine (OneClass-SVM)—and a traditional supervised algorithm, Support Vector Machine…”
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  10. 10

    Artificial Intelligence-Enabled End-To-End Detection and Assessment of Alzheimer’s Disease Using Voice Autor Agbavor, Felix, Liang, Hualou

    ISSN: 2076-3425, 2076-3425
    Vydáno: Switzerland MDPI AG 23.12.2022
    Vydáno v Brain sciences (23.12.2022)
    “… At the core of our system is the pre-trained data2vec model, the first high-performance self-supervised algorithm that works for speech, vision, and text…”
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  11. 11

    Motor Function Evaluation of Hemiplegic Upper-Extremities Using Data Fusion from Wearable Inertial and Surface EMG Sensors Autor Li, Yanran, Zhang, Xu, Gong, Yanan, Cheng, Ying, Gao, Xiaoping, Chen, Xiang

    ISSN: 1424-8220, 1424-8220
    Vydáno: Switzerland MDPI AG 13.03.2017
    Vydáno v Sensors (Basel, Switzerland) (13.03.2017)
    “…) and surface electromyography (EMG) sensors. With wearable sensors worn on the tested upper limbs, subjects were asked to perform eleven straightforward, specifically designed canonical upper-limb functional tasks…”
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  12. 12

    Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI Autor Otte, Georges, Wyns, Bart, Grosse-Wentrup, Moritz, Santens, Patrick, Devlaminck, Dieter

    ISSN: 1687-5265, 1687-5273, 1687-5273
    Vydáno: Cairo, Egypt Hindawi Limiteds 01.01.2011
    “…) as preprocessing step before feature extraction and classification. The CSP method is a supervised algorithm and therefore needs subject-specific training data for calibration, which is very time consuming to collect…”
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  13. 13

    A Machine Vision Method for Automated Alignment of Fundus Imaging Systems Autor Moscaritolo, Michele, Knezevich, Frederick P., Zimmer-Galler, Ingrid, Jampel, Henry, Zeimer, Ran

    ISSN: 1542-8877, 2325-8160, 1938-2375, 2325-8179, 1938-2375
    Vydáno: Thorofare, NJ SLACK Incorporated 01.11.2010
    Vydáno v Ophthalmic surgery, lasers & imaging (01.11.2010)
    “… The system consists of two cameras acquiring pupil images from two distinct directions and an operator-supervised algorithm to derive the coordinates of the pupil center and output of commands…”
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  14. 14

    A large margin algorithm for automated segmentation of white matter hyperintensity Autor Qin, Chen, Guerrero, Ricardo, Bowles, Christopher, Chen, Liang, Dickie, David Alexander, Valdes-Hernandez, Maria del C., Wardlaw, Joanna, Rueckert, Daniel

    ISSN: 0031-3203, 1873-5142
    Vydáno: Elsevier Ltd 01.05.2018
    Vydáno v Pattern recognition (01.05.2018)
    “…•A supervised large margin algorithm is proposed to learn a global classifier.•A semi-supervised large margin classifier is learned for refinement on test subject…”
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  15. 15

    Quasi-supervised scoring of human sleep in polysomnograms using augmented input variables Autor Yaghouby, Farid, Sunderam, Sridhar

    ISSN: 0010-4825, 1879-0534, 1879-0534
    Vydáno: United States Elsevier Ltd 01.04.2015
    Vydáno v Computers in biology and medicine (01.04.2015)
    “… EEG, EMG, and EOG features were extracted in 30s epochs from human-scored polysomnograms recorded from 42 healthy human subjects (18–79 years…”
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  16. 16

    Colorectal Cancer Tissue Classification Using Semi-Supervised Hypergraph Convolutional Network Autor Bakht, Ahsan Baidar, Javed, Sajid, AlMarzouqi, Hasan, Khandoker, Ahsan, Werghi, Naoufel

    ISSN: 1945-8452
    Vydáno: IEEE 13.04.2021
    “… In this paper, we propose a semi-supervised algorithm for CRC tissue classification. We propose to employ the hypergraph neural network to classify seven different biologically meaningful CRC tissue types…”
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  17. 17

    Two distributed semi-supervised algorithms for mining of complex networks using Giraph Autor Erfan Farhangi Maleki, Ghadiri, Nasser, Maryam Lotfi Shahreza, Maleki, Zeinab

    ISSN: 2692-8205, 2692-8205
    Vydáno: Cold Spring Harbor Cold Spring Harbor Laboratory Press 15.11.2019
    Vydáno v bioRxiv (15.11.2019)
    “…Heterogeneous networks are large graphs consisting of different types of nodes and edges. They are an important category of complex networks, but the process…”
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  18. 18

    Disease classification and prediction via semi-supervised dimensionality reduction Autor Batmanghelich, K N, Ye, D H, Pohl, K M, Taskar, B, Davatzikos, C

    ISBN: 1424441277, 9781424441273
    ISSN: 1945-7928, 1945-8452
    Vydáno: United States IEEE 01.03.2011
    “…We present a new semi-supervised algorithm for dimensionality reduction which exploits information of unlabeled data in order to improve the accuracy of image-based disease classification based on medical images…”
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  19. 19

    Decoding EEG in Motor Imagery Tasks with Graph Semi-Supervised Broad Learning Autor She, Qingshan, Zhou, Yukai, Gan, Haitao, Ma, Yuliang, Luo, Zhizeng

    ISSN: 2079-9292, 2079-9292
    Vydáno: Basel MDPI AG 01.11.2019
    Vydáno v Electronics (Basel) (01.11.2019)
    “…In recent years, the accurate and real-time classification of electroencephalogram (EEG) signals has drawn increasing attention in the application of…”
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  20. 20

    Supervised Machine Learning Approaches to Identify the False and True News from Social Media Data Autor Sadik, Md Rezwane, Rana, Md Masum, Akter, Lima, Islam, Rafiul, Rahman, Md. Hasanur, Rahman, Md. Musfiqur

    Vydáno: IEEE 23.02.2024
    “… Before passing judgment on the accuracy of a piece, even a subject matter specialist needs to look into a number of different angles…”
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