https://www.selleckchem.com/products/tpi-1.html
PSAT-GAN is further enhanced by applying novel adversarial and soft-constraint losses to generate effective perturbations and avoid studying transferability. Experimental results indicate that our method is efficient in generating both universal and image-dependent adversarial examples to fool HSU tasks under either targeted or non-targeted settings.Despite the great success achieved by prevailing binary local descriptors, they are still suffering from two problems 1) vulnerable to the geometric transformations; 2) lack of an effective tr
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