Visual Recognition applies image recognition algorithms to your content to detect relevant features and automatically apply "Concepts".
Concepts are similar to Tags however they are simpler, text-only labels and can be controlled and managed separately from Tags so as not to complicate your Tagging strategy.
How to configure Visual Recognition
Navigate to Settings > Visual Recognition.
There is a single configuration screen for Visual Recognition, all your available options are found here.
Automatically apply to selected terms
From this dropdown, you can select which one or more of your Terms you would like to apply Visual Recognition to.
NB: You can also choose to apply Visual Recognition to a Term when creating or editing a Term, you'll find the option on the Advanced tab.
Only apply concepts with ≥ X% confidence
As the description states, each Concept that Visual Recognition identifies comes with an estimate of how accurate it is - this is called "confidence".
Choosing a higher confidence level eg. 95% will ensure the Concepts applied to your content are more accurate but typically you will receive fewer. Lowering the confidence will result in more Concepts being applied however the accuracy of some may be lower.
You can test different confidence levels by selecting from the dropdown and then observing the results in the Concepts Preview window below.
Rate Limit
The information found here shows you how many images you can apply Visual Recognition to each month, how many you have used, and how many days are left until your monthly quota is refreshed.
Advanced Visual Recognition Additional Options
With UGC's Advanced Visual Recognition, you will have access to several custom models that are trained to identify specific subcategories of objects.
Video Processing
This option applies Visual Recognition to Instagram, Twitter, and Direct Uploader-uploaded videos.
Advanced Visual Recognition Models
Advanced Visual Recognition provides you with access to several specialty models that have been trained for specific types of content.
You can read more about these models here.
For any further questions or queries, please send an email to support@nosto.com and our support team will get back to you.