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Created: 23/03/10 @ 13:19:35 | Last updated: 10/01/12 @ 08:47:41
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License: Creative Commons Attribution-Share Alike 3.0 Unported License
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Rating: 0.0 / 5 (0 ratings) | Versions: 3 | Reviews: 0 | Comments: 0 | Citations: 0 Viewed: 200 times | Downloaded: 51 times Tags (4): |
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Original Uploader |
Created: 28/04/10 @ 11:00:37 | Last updated: 16/01/12 @ 14:16:23 License: Creative Commons Attribution-No Derivative Works 3.0 Unported License
This is an image mining process using the image mining Web service provided by NHRF within e-Lico. It first uploads a set of images found in a directory, then preprocesses the images and visualizes the result. Furthermore, references to the uploaded images are stored in the local RapidMiner repository so they can later be used for further processing without uploading images a second time.
Rating: 0.0 / 5 (0 ratings) | Versions: 1 | Reviews: 0 | Comments: 1 | Citations: 0 Viewed: 734 times | Downloaded: 346 times Tags (5): |
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Original Uploader |
Created: 08/09/11 @ 22:04:03 | Last updated: 09/09/11 @ 09:00:18
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License: Creative Commons Attribution-No Derivative Works 3.0 Unported License
This process is simple example of local feature extraction with model traininig (using SVM and X-validation). Input is grayscale source image and image mask. White places are true and black false.
This workflow needs IMMI - Rapidminer 5 Image Processing Extension.
Rating: 0.0 / 5 (0 ratings) | Versions: 1 | Reviews: 0 | Comments: 0 | Citations: 0 Viewed: 32 times | Downloaded: 24 times Tags (4): |
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Original Uploader |
Created: 08/09/11 @ 21:54:51 | Last updated: 09/09/11 @ 09:00:58
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License: Creative Commons Attribution-No Derivative Works 3.0 Unported License
This process is simple example of local feature extraction with no model training. Input is grayscale source image and image mask. White places are true and black false.
This workflow needs IMMI - Rapidminer 5 Image Processing Extension.
Rating: 0.0 / 5 (0 ratings) | Versions: 1 | Reviews: 0 | Comments: 0 | Citations: 0 Viewed: 26 times | Downloaded: 16 times Tags (4): |
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Original Uploader |
Created: 08/09/11 @ 22:02:19 | Last updated: 09/09/11 @ 08:59:20
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License: Creative Commons Attribution-No Derivative Works 3.0 Unported License
This process is simple example of local feature extraction with no model training. Input is grayscale source image and image mask. White places are true and black false. Thresholdig operator is used to limit processed pixels only to non black (values greater than 0).
This workflow needs IMMI - Rapidminer 5 Image Processing Extension.
Rating: 0.0 / 5 (0 ratings) | Versions: 1 | Reviews: 0 | Comments: 0 | Citations: 0 Viewed: 46 times | Downloaded: 16 times Tags (4): |
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Original Uploader |
Created: 09/09/11 @ 10:28:01 | Last updated: 09/09/11 @ 10:29:20
Credits:
License: Creative Commons Attribution-No Derivative Works 3.0 Unported License
This process is simple example of apply trained model to mined data from image. Results are performance and probability visualization.
This workflow needs IMMI - Rapidminer 5 Image Processing Extension.
Rating: 0.0 / 5 (0 ratings) | Versions: 1 | Reviews: 0 | Comments: 0 | Citations: 0 Viewed: 43 times | Downloaded: 20 times Tags (4): |
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