When artificial intelligence systems encounter scenes where objects are not fully visible, they have to make estimations based only on the visible parts of the objects. This partial information leads to detection errors, and large training data is required to correctly recognize such scenes. Now, researchers at the Gwangju Institute of Science and Technology have developed a framework that allows robot vision to detect such objects successfully in the same way that we perceive them
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