Object Reidentification via Joint Quadruple Decorrelation Directional Deep Networks in Smart Transportation
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DOI: 10.1109/jiot.2020.2963996
Abstract: Object reidentification with the goal of matching pedestrian or vehicle images captured from different camera viewpoints is of considerable significance to public security. Quadruple directional deep learning features (QD-DLFs) can comprehensively describe object images. However,… read more here.
Keywords: directional deep; deep networks; object reidentification; correlation among ... See more keywords