Process of training the artificial intelligence model based on the collected data.
What kind of categories should AI recognize? Examples:
Gathering named photo sets can be managed through a special mobile application that can be easily installed on the smartphone.
Every photo needs to be properly categorized by choosing it’s category manually.
After documenting, each photo is sent to the archive in the cloud where our algorithm will use them to learn to classify chosen objects.
>Process of training the artificial intelligence model based on the collected data.
Choosing the right CNN architecture is crucial to be able to get the best results to recognize images.
Choosing proper hyperparameters to a given CNN architecture and adjusting them to get the best results.
This allows to test in the conditions that will be later present later while being able to control the results and adjust steps 1 and 2 if needed.
Deployment process of the trained model and integration with existing systems and devices
The model with it’s API can be Choosing the right CNN architecture is crucial to be able to get the best results to recognize images.
In order to control access, billing, configuration of basic parameters, admins have the ability to manage the mechanism through a web portal.
System can communicate with a any chosen software, thanks so the ability to create dedicated integrations.
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