Buren 发表于 2025-3-21 19:10:53
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for them to be deployed in security-sensitive applications, such as autonomous driving. Image-dependent perturbations can fool a network for one specific image, while universal adversarial perturbations are capable of fooling a network for samples from all classes without selection. We introduce anutrients 发表于 2025-3-22 04:25:24
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Takahiro Fujimoto work, we explore learning from abundant, randomly generated synthetic data, together with unlabeled or partially labeled target domain data, instead. Randomly generated synthetic data has the advantage of controlled variability in the lane geometry and lighting, but it is limited in terms of photo-Admonish 发表于 2025-3-22 18:13:18
Hirofumi Tatsumotoailed spectral distribution helping for numerous applications. However, existing HS imaging sensor can only obtain images with low spatial resolution. Thus fusing a low resolution hyperspectral (LR-HS) image with a high resolution (HR) RGB (or multispectral) image into a HR-HS image has received muc拉开这车床 发表于 2025-3-23 00:09:40
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