Presentation is loading. Please wait.

Presentation is loading. Please wait.

Feature Extraction Find best Alignment between primitives and data Found Alignment? TUH EEG Corpus Supervised Learning Process Reestimate Parameters Recall.

Similar presentations


Presentation on theme: "Feature Extraction Find best Alignment between primitives and data Found Alignment? TUH EEG Corpus Supervised Learning Process Reestimate Parameters Recall."— Presentation transcript:

1 Feature Extraction Find best Alignment between primitives and data Found Alignment? TUH EEG Corpus Supervised Learning Process Reestimate Parameters Recall Parameters Input: EEG raw data Output: Model Parameters

2 Feature Extraction Find best alignment between primitives and data Alignment Found? Recall Parameters Supervised learning process Reestimate Parameters TUH EEG Corpus Input: EEG Raw Data Output: Model Parameters

3 Feature Extraction Find best Alignment between primitives and data Found Alignment? TUH EEG Corpus Supervised Learning Process Reestimate Parameters Recall Parameters Input: EEG raw data Output: Model Parameters

4 Copy EEG Files to Disks Convert EEG files to EDF Capture Physicians Reports Label Generation MModal DatabaseDeidentify Reports Alpha Database Hard Copies Optical Character Recognition Manual Correction

5 Copy EEG Files to Disks Convert EEG files to EDF Capture Physicians Reports Deidentify ReportsLabel Generation Hard CopiesAlpha DatabaseMModal Database Optical Character Recognition Manual Correction

6 Copy EEG files to Disks Convert EEG files to EDF Capture Physicians' Reports Deidentify ReportsLabel Generation Hard Copies Alpha Database M*Modal Database Optical Character Recognition Copy EEG files to Disks Access Database


Download ppt "Feature Extraction Find best Alignment between primitives and data Found Alignment? TUH EEG Corpus Supervised Learning Process Reestimate Parameters Recall."

Similar presentations


Ads by Google