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pro vyhledávání: '"Tang, Weiheng"'
Diffusion models have demonstrated exceptional ability in modeling complex image distributions, making them versatile plug-and-play priors for solving imaging inverse problems. However, their reliance on large-scale clean datasets for training limits
Externí odkaz:
http://arxiv.org/abs/2410.11241
Autor:
Kreiss, Lucas, Tang, Weiheng, Balla, Ramana, Yang, Xi, Chaware, Amey, Kim, Kanghyun, Cook, Clare B., Begue, Aurelien, Dugo, Clay, Harfouche, Mark, Zhou, Kevin C., Horstmeyer, Roarke
We present an approach of utilizing a multi-camera array system for capturing dynamic high-resolution videos of the human face, with improved imaging performance as compared to traditional single-camera configurations. Employing an array of 54 indivi
Externí odkaz:
http://arxiv.org/abs/2410.01973
Edge computing has recently emerged as a promising paradigm to boost the performance of distributed learning by leveraging the distributed resources at edge nodes. Architecturally, the introduction of edge nodes adds an additional intermediate layer
Externí odkaz:
http://arxiv.org/abs/2406.10831