Abstract: This work investigates the problem of efficiently learning discriminative low-dimensional (LD) representations of multiclass image objects. We propose a generic end-to-end approach that ...
Corrales, a recent biological sciences Ph.D. graduate from the University of Rhode Island, and his advisor, Associate ...
Abstract: Current deep learning-based steganalyzers often depend on specific image dimensions, leading to inevitable adjustments in network structure when dealing with varied image sizes. This impedes ...
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