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Handling Visual Parameters

The post articulates how Visual Learning works at a high level within the RM2 Platform. The Visual learning feature in RM2 is integrated into the unified architecture where visual object detection and learning are integrated to achieve real-time detection and behavior prediction in a given environment.

In order to accurately detect objects and learn from correct data associations, it is critical to extract unit data parameters for the development of a proper foundation for the establishment of a relationship between unique parameters. This approach will result in high accuracy for the identification of objects, or for learning object behavior.