New feature to Watson Visual Recognition improves visual classifiers
Recently, IBMer Andy Trice developed a great application demonstrating how to use drones and Watson Visual Recognition to conduct areal surveys. We thought it would be even more impactful if the drone could get smarter using real time feedback from pilots on the ground. This would enable a truly a symbiotic relationship between cognitive computing and humans.
Today, we are excited to introduce a new feature to Watson Visual Recognition that allows users to continue improving visual classifiers. When a user submits an image and Watson Visual Recognition returns a score, users can now continue inputting new images, giving Watson additional examples to learn from. In layman terms, Watson Visual Recognition can now learn over time, continuously getting better at understanding visual information. Here is an example of how it works.
Andy agreed that this would be a great improvement and even went ahead an incorporated the functionality into the demonstration! Replicate for your self using his code.
Get started now! Check out the new Retraining feature here