Výsledky vyhľadávania - Novel Methods for 3D Data Compression with Comparative Analysis via the Fourier Transform

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  1. 1

    A Comparative Analysis of the Lossless Data Compression Methods for Unsparsed Tabular Data Autor Erkus, Ekin Can, Bursali, Ahmet

    Vydavateľské údaje: IEEE 25.07.2024
    “…This paper conducts a comparative analysis of the impact of unsparsing by data scaling on lossless data compression methods…”
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    Comparative Analysis of K-RLE and LTC Methods for Measurement Data Compression with Losses Control Autor Semenov, Konstantin, Raimzhanova, Adele

    Vydavateľské údaje: IEEE 28.05.2025
    “…The requirements imposed by metrology on measurement results restrict the feasibility of their archiving when large data volumes are involved - notably if one uses lossy compression methods…”
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    Comparative Analysis of Statistical Test Based on Data Compression Methods and Standard Tests for Assessing Randomness of Random Number Generators Autor Lulu, Yeshewas Getachew

    ISSN: 2995-0996
    Vydavateľské údaje: IEEE 30.09.2024
    “…This paper presents a detailed comparative analysis of statistical tests utilizing both modern data compressors and standard statistical methods for assessing the randomness of Ran-dom number generators(RNG…”
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  4. 4

    A novel smart meter data compression method via stacked convolutional sparse auto-encoder Autor Wang, Shouxiang, Chen, Haiwen, Wu, Lei, Wang, Jianfeng

    ISSN: 0142-0615
    Vydavateľské údaje: Elsevier Ltd 01.06.2020
    “… In this paper, a deep-learning-based compression method for smart meter data is proposed via stacked convolutional sparse auto-encoder (SCSAE…”
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    Journal Article
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    Comparative Analysis of Deep Argo in Situ Data With a Novel Extrapolation Method & Illustration of Anomalies Autor Piao, Shengchun, Iqbal, Kashif, Zhang, Minghui, Nansong, Li

    Vydavateľské údaje: IEEE 05.10.2020
    “… The need for this particular activity was compelled by requirement of weather-related ocean data desired by the oceanographic researchers around the world…”
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    A novel, objective, quantitative method of evaluation of the back pain component using comparative computerized multi-parametric tactile mapping before/after spinal cord stimulation and database analysis: The “Neuro-Pain’t” software Autor Rigoard, P., Nivole, K., Blouin, P., Monlezun, O., Roulaud, M., Lorgeoux, B., Bataille, B., Guetarni, F.

    ISSN: 0028-3770, 1773-0619, 1773-0619
    Vydavateľské údaje: France Elsevier Masson SAS 01.03.2015
    Vydané v Neuro-chirurgie (01.03.2015)
    “…One of the major challenges of neurostimulation is actually to address the back pain component in patients suffering from refractory chronic back and leg pain…”
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    Journal Article
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    On the performance of surface electromyography-based onset detection methods with real data in assistive technologies: Comparative analysis and enhancements via sensor fusion Autor Reis, Margarida, Almeida, Carlos, Rocha, Rui M.

    ISSN: 1380-7501, 1573-7721
    Vydavateľské údaje: New York Springer US 01.05.2018
    Vydané v Multimedia tools and applications (01.05.2018)
    “… In the literature, various methods to determine this onset have been studied, but mainly for the non-disabled population and may not be designed to deal with the low signal-to-noise ratio, motion…”
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    Journal Article
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    A Novel, Objective, Quantitative Method of Evaluation of the Pain Component and Paresthesia Coverage using Comparative Computerized Multiparametric Tactile Mapping and Database Analysis: The “Neuro-Mapping-Tools” Software (N3MT) Autor Roulaud, Manuel, Guetarni, Farid, Nivole, Kévin, Monlezun, Olivier, Lorgeoux, Bertille, Rigoard, Philippe

    ISSN: 2192-5682, 2192-5690
    Vydavateľské údaje: Los Angeles, CA SAGE Publications 01.04.2016
    Vydané v Global spine journal (01.04.2016)
    “… and neurostimulation outcomes for those who undergo neurostimulation implantation. Material and Methods Our neuroinformatics laboratory (N3Laboratory…”
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    Journal Article
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    Optimizing Parkinson’s Disease Prediction: A Comparative Analysis of Data Aggregation Methods Using Multiple Voice Recordings via an Automated Artificial Intelligence Pipeline Autor Yang, Zhengxiao, Zhou, Hao, Srivastav, Sudesh, Shaffer, Jeffrey G., Abraham, Kuukua E., Naandam, Samuel M., Kakraba, Samuel

    ISSN: 2306-5729, 2306-5729
    Vydavateľské údaje: Basel MDPI AG 01.01.2025
    Vydané v Data (Basel) (01.01.2025)
    “… This study compares four data aggregation methods designed to tackle the grouped structure in classification tasks…”
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    Journal Article
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    Stability analysis of sampled-data systems via novel Lyapunov functional method Autor Sheng, Zhaoliang, Lin, Chong, Chen, Bing, Wang, Qing-Guo

    ISSN: 0020-0255, 1872-6291
    Vydavateľské údaje: Elsevier Inc 01.03.2022
    Vydané v Information sciences (01.03.2022)
    “…This study focuses on the stability analysis of sampled-data systems. The idea is to propose a novel Lyapunov functional method using a new framework…”
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    Journal Article
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    A Novel Classification Method for Analysis of Multi-stage Diseases via Mass Spectrometric Data Autor Oh, Jung Hun, Kim, Young Bun, Gao, Jean

    ISBN: 0769530311, 9780769530314
    Vydavateľské údaje: IEEE 01.01.2007
    “…Multi-category classification is one of the challenging issues in medical data analysis…”
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    Novel feature selection method via kernel tensor decomposition for improved multi-omics data analysis Autor Y-H, Taguchi, Turki, Turki

    ISSN: 2692-8205, 2692-8205
    Vydavateľské údaje: Cold Spring Harbor Cold Spring Harbor Laboratory Press 17.12.2021
    Vydané v bioRxiv (17.12.2021)
    “…Background: Feature selection of multi-omics data analysis remains challenging owing to the size of omics datasets, comprising approximately 102-105 features…”
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    Novel feature selection method via kernel tensor decomposition for improved multi-omics data analysis Autor Taguchi, Y-h., Turki, Turki

    ISSN: 1755-8794, 1755-8794
    Vydavateľské údaje: London BioMed Central 24.02.2022
    Vydané v BMC medical genomics (24.02.2022)
    “…Background Feature selection of multi-omics data analysis remains challenging owing to the size of omics datasets, comprising approximately 10 2 – 10 5 features…”
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    Journal Article
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