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- Timestamp:
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11/23/12 18:52:08 (11 years ago)
- Author:
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spli
- Comment:
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| 11 | 11 | |
| 12 | 12 | OMERO.searcher and WND-CHRM will be used to develop and evaluate the API, and will also form reference implementations/examples. |
| | 13 | |
| | 14 | == Workflow == |
| | 15 | The general workflow from a user's point of view is as follows: |
| | 16 | 1. Preprocess images #9947 |
| | 17 | 2. Calculate image features, store them #9948 |
| | 18 | 3. Train an algorithm to understand images #9949 |
| | 19 | 4. Use the trained algorithm to make predictions or search images #9951 |
| | 20 | 5. View the results #9952 |
| | 21 | |
| | 22 | Depending on the algorithm some of these steps will be transparent to a user. For example, a general search application such as OMERO.searcher may continuously run in the background, automatically calculating features and updating its knowledge, so a user would only be exposed to the search interface. |
| | 23 | |
| | 24 | A data-exploration tool might effectively build any machine learning into the visualisation stage for real-time exploration. This means only the feature extraction and visualisation steps are required. |
| | 25 | |
| | 26 | The context of a learning algorithm (#9950) will require some thought to make it usable by non-specialists. |
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