We invite you to shape the future of IBM, including product roadmaps, by submitting ideas that matter to you the most. Here's how it works:
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The IBM team may need your help to refine the ideas so they may ask for more information or feedback. The product management team will then decide if they can begin working on your idea. If they can start during the next development cycle, they will put the idea on the priority list. Each team at IBM works on a different schedule, where some ideas can be implemented right away, others may be placed on a different schedule.
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Some ideas can be implemented at IBM, while others may not fit within the development plans for the product. In either case, the team will let you know as soon as possible. In some cases, we may be able to find alternatives for ideas which cannot be implemented in a reasonable time.
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Features such as custom classifiers and general tagging don't work well when there's multiple objects within a scene, or the objects that need to be classified take up less than 1/3rd of the area of an image.
When I get low classification scores from a custom classifier I trained, I would like to know how I can improve the classifier's accuracy. Even better would be knowing which training images are potentially dragging the score down.
Ideally I wouldn't need to do training for Watson to recognize my logo, but if it is needed, I wouldn't mind uploading a small number of images of my logo (<10 images) to train the system. Watson should be able to identify multiple instances of...
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