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  2. CAM2 software for hearing aid fitting – Cambridge Enterprise

    https://www.enterprise.cam.ac.uk/reagents/cam2-software-for-hearing-aid-fitting/
    Thumbnail for CAM2 software for hearing aid fitting – Cambridge Enterprise 9 May 2022: Mobile menu. Mobile menu. Search. back. back. back. back. CAM2 software for hearing aid fitting. ... field. CAM2 is available for licensing to hearing aid manufacturers and providers and for academic research purposes.
  3. CAM2 hearing aid fitting software available from University of…

    https://licensing.enterprise.cam.ac.uk/product/cam2-hearing-aid-fitting-software
    Your basket is empty. search. CAM2 software is a package that enables hearing aids to be tailored to an individual’s needs, resulting in improved hearing quality. ... field. CAM2 is available for licensing to hearing aid manufacturers and providers and
  4. Workspace | Cambridge Advanced Modeller 2

    https://camtoolkit.eng.cam.ac.uk/workspace_change
    30 Apr 2024: Search site. Cambridge Advanced Modeller 2. Workspace. Workspace. Each file contains exactly one workspace. The workspace provides the 'box' within which all collections (models) are collected. Within a workspace, certain information is shared
  5. Workspace | Cambridge Advanced Modeller 2

    https://camtoolkit.eng.cam.ac.uk/workspace-1
    30 Apr 2024: Search site. Cambridge Advanced Modeller 2. Workspace. Workspace. Each file contains exactly one workspace. The workspace provides the 'box' within which all collections (models) are collected. Within a workspace, certain information is shared
  6. Visual Analytics Tutorial: Selection Tools | Cambridge Advanced…

    https://camtoolkit.eng.cam.ac.uk/visual-analytics/visual-analytics-tutorial/visual-analytics-tutorial-selection-tools
    30 Apr 2024: Search site. Cambridge Advanced Modeller 2. Visual Analytics Tutorial: Selection Tools. PCX selection tools allow the designer to highlight and bring to focus individual datapoints as well as subsets of the loaded dataset. These features help in
  7. Visual Analytics Tutorial: Plot Options | Cambridge Advanced Modeller …

    https://camtoolkit.eng.cam.ac.uk/visual-analytics/visual-analytics-tutorial/visual-analytics-tutorial-plot-options
    30 Apr 2024: Search site. Cambridge Advanced Modeller 2. Visual Analytics Tutorial: Plot Options. Plot Options are PCX features which adjust the display settings to tailor-fit the designer's requirements. They aid in distinguishing between points, decluttering
  8. Visual Analytics Tutorial: Machine Learning | Cambridge Advanced…

    https://camtoolkit.eng.cam.ac.uk/visual-analytics/visual-analytics-tutorial/visual-analytics-tutorial-machine-learning
    30 Apr 2024: Search site. Cambridge Advanced Modeller 2. Visual Analytics Tutorial: Machine Learning. PCX is equipped with Machine Learning tools which support and improve the analysis and assess associated risks. Select Output Axes: Select output variables by
  9. Visual Analytics Tutorial: Data | Cambridge Advanced Modeller 2

    https://camtoolkit.eng.cam.ac.uk/visual-analytics/visual-analytics-tutorial/visual-analytics-tutorial-data
    30 Apr 2024: Search site. Cambridge Advanced Modeller 2. Visual Analytics Tutorial: Data. The PCX data tools relate to viewing and saving the analysis information. View Dataset: Display raw data included in the current selection in a table. Export CSV: Export
  10. Visual Analytics Tutorial | Cambridge Advanced Modeller 2

    https://camtoolkit.eng.cam.ac.uk/visual-analytics/visual-analytics-tutorial
    30 Apr 2024: Search site. Cambridge Advanced Modeller 2. Visual Analytics Tutorial. Tutorial. Using PCX for Visual Analysis. The PCX toolkit provides the designer with full control over the visualisation of the data. A wide range of parameters can be adjusted to
  11. Visual Analytics Literature | Cambridge Advanced Modeller 2

    https://camtoolkit.eng.cam.ac.uk/visual-analytics/visual-analytics-literature
    30 Apr 2024: Search site. Cambridge Advanced Modeller 2. Visual Analytics Literature. Enhanced Interactive Parallel Coordinates using Machine Learning and Uncertainty Propagation for Engineering Design, Wiktor Piotrowski, Timoleon Kipouros, P John Clarkson, IEEE

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