Showing 201 - 220 results of 277 for search '"UC Irvine"', query time: 0.21s Refine Results
  1. 201

    A Generative Adversarial Network Structure for Learning with Small Numerical Data Sets by Der-Chiang Li, Szu-Chou Chen, Yao-San Lin, Kuan-Cheng Huang

    Published 2021-11-01
    “…The model verification of our proposed structure was conducted with two datasets in the UC Irvine Machine Learning Repository, and the performance was evaluated using three criteria: accuracy, standard deviation, and <i>p</i>-value. …”
    Get full text
    Article
  2. 202

    A generative adversarial network structure for learning with small numerical data sets by Li, Der-Chiang, Chen, Szu-Chou, Lin, Yao-Sin, Huang, Kuan-Cheng

    Published 2022
    “…The model verification of our proposed structure was conducted with two datasets in the UC Irvine Machine Learning Repository, and the performance was evaluated using three criteria: accuracy, standard deviation, and p‐value. …”
    Get full text
    Journal Article
  3. 203
  4. 204

    Comparison of Automated Machine Learning (AutoML) Tools for Epileptic Seizure Detection Using Electroencephalograms (EEG) by Swetha Lenkala, Revathi Marry, Susmitha Reddy Gopovaram, Tahir Cetin Akinci, Oguzhan Topsakal

    Published 2023-09-01
    “…The study compares the performance of three different AutoML tools, AutoGluon, Auto-Sklearn, and Amazon Sagemaker, on three different datasets from the UC Irvine ML Repository, Bonn EEG time series dataset, and Zenodo. …”
    Get full text
    Article
  5. 205
  6. 206

    MyoNet: A Transfer-Learning-Based LRCN for Lower Limb Movement Recognition and Knee Joint Angle Prediction for Remote Monitoring of Rehabilitation Progress From sEMG by Arvind Gautam, Madhuri Panwar, Dwaipayan Biswas, Amit Acharyya

    Published 2020-01-01
    “…The proposed MyoNet was evaluated on publicly available University of California (UC) Irvine machine learning repository dataset of the lower limb for 11 healthy subjects and 11 subjects with knee pathology for three movements type-walking, standing with knee flexion movements and sitting with knee extension movements. …”
    Get full text
    Article
  7. 207
  8. 208
  9. 209
  10. 210
  11. 211

    Adagrasib in KRYSTAL-12&nbsp;has Not Broken the KRAS G12C Enigma Code of the Unspoken 6-Month PFS Barrier in NSCLC by Lee AT, Nagasaka M

    Published 2024-12-01
    “…Marianna University School of Medicine, Department of Medicine, Kawasaki, JapanCorrespondence: Misako Nagasaka, Department of Medicine, Division of Hematology/Oncology, UC Irvine, Orange, CA, 92602, USA, Email nagasakm@hs.uci.eduAbstract: Mutations in KRAS G12C are among the more common oncogenic driver mutations in non-small cell lung cancer (NSCLC). …”
    Get full text
    Article
  12. 212
  13. 213
  14. 214
  15. 215
  16. 216
  17. 217
  18. 218

    Automated time activity classification based on global positioning system (GPS) tracking data by Wu Jun, Jiang Chengsheng, Houston Douglas, Baker Dean, Delfino Ralph

    Published 2011-11-01
    “…</p> <p>Methods</p> <p>We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. …”
    Get full text
    Article
  19. 219
  20. 220