AAAI Publications, Workshops at the Twenty-Fourth AAAI Conference on Artificial Intelligence

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Estimating Quantitative Magnitudes Using Semantic Similarity
Jim Davies, Jonathan Gagne

Last modified: 2010-07-07

Abstract


We present an AI called Visuo that guesses quantitative visuospatial magnitudes (e.g., heights, lengths) given adjective-noun pairs as input (e.g., “big hat”). It uses a database of tagged images as memory and infers unexperienced magnitudes by analogy with semantically-related concepts in memory. We show that transferring width-height ratios from a semantically-related concept yields significantly lower error rates than using dissimilar concepts when predicting the width-height ratios of novel inputs.

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