Halfhearted
发表于 2025-3-30 09:06:50
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不容置疑
发表于 2025-3-30 15:27:00
https://doi.org/10.1007/978-1-349-00463-8ing the projected samples and generating synthetic images by interpolating the cluster centroids, thus reducing the possibility of collision with latent vectors corresponding to real samples and a consequent leak of sensitive information. The proposed approach is tested over two X-ray datasets for T
Malcontent
发表于 2025-3-30 20:33:30
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drusen
发表于 2025-3-31 00:17:28
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柔美流畅
发表于 2025-3-31 04:12:27
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Self-Help-Group
发表于 2025-3-31 08:35:38
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Aerophagia
发表于 2025-3-31 12:26:39
https://doi.org/10.1007/978-1-4684-6724-6ing environments with highly heterogeneous data distributions. One surprising benefit of model pruning is improved model privacy. We demonstrate that models with high sparsity are less susceptible to membership inference attacks, a type of privacy attack.
Volatile-Oils
发表于 2025-3-31 16:56:10
https://doi.org/10.1007/978-1-4684-6724-6r resolution, scanning rate, and imaging depth than a commercial OCT system. We use generative adversarial networks (GANs) to enhance the quality of this p-OCT data and then assess the impact of this enhancement on downstream performance of artificial intelligence (AI) algorithms for AMD detection.
insular
发表于 2025-3-31 18:01:31
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地壳
发表于 2025-3-31 22:48:57
Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource DiThird MICCAI Worksho