Researchers at Leiden University and the National University of Defense Technology (NUDT), in China, have recently developed a new approach for image-text matching, called CycleMatch. Their approach, presented in a paper published in Elsevier's Pattern Recognition journal, is based on cycle-consistent learning, a technique that is sometimes used to train artificial neural networks on image-to-image translation tasks. The general idea behind cycle-consistency is that when transforming source data into target data and then vice versa, one should finally obtain the original source samples.
from News on Artificial Intelligence and Machine Learning http://bit.ly/2X296ig
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CycleMatch: a new approach for matching images and text
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