Embodied Object Representation Learning and Recognition.

ABSTRACT: Scene understanding and decomposition is a crucial challenge for intelligent systems, whether it is for object manipulation, navigation, or any other task. Although current machine and deep learning approaches for object detection and classification obtain high accuracy, they typically do not leverage interaction with the world and are limited to a set of objects seen during training. Humans on the other hand learn to recognize and classify different objects by actively engaging with them on first encounter. Moreover, recent theories in neuroscience suggest that cortical columns in the neocortex play an important role in this process, by building predictive models about objects in their reference frame. In this article, we present an enactive embodied agent that implements such a generativ

SUBMITTER: Van de Maele T 

PROVIDER: S-EPMC9049856 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature