Jun 12, 2024 · In formulation, SSD-KD introduces a modulating function to balance synthetic samples and a priority sampling function to select proper samples, facilitated by a dynamic …

Mar 22, 2022 · To bridge the gap, this study specifically proposes a novel method, termed SSD-KD, that unifies diverse knowledge into a generic KD framework for skin diseases …

In formulation, SSD-KD introduces a modulating function to balance synthetic samples and a priority sampling function to select proper samples, facilitated by a dynamic replay buffer and a …

To bridge the gap, this study specifically proposes a novel method, termed SSD-KD, that unifies diverse knowledge into a generic KD framework for skin diseases classification. Our method …

ssd-kd是一种完全高效的d-kd方法，能够使用极小规模的合成数据，同时与现有的d-kd方法相比，达到具有竞争力的性能。 ssd-kd的流程总结在算法1中，现有对抗性d-kd方法的优化流程（ …

In light of three empirical observations indicating the importance of how to balance class distributions in terms of synthetic sample di-versity and dificulty during both data inversion and …

Feb 1, 2023 · To bridge the gap, this study specifically proposes a novel method, termed SSD-KD, that unifies diverse knowledge into a generic KD framework for skin disease classification. …

To bridge the gap, this study specifically proposes a novel method, termed SSD-KD, that unifies diverse knowledge into a generic KD framework for skin disease classification. Our method …

In light of three empirical observations indicating the importance of how to balance class distributions in terms of synthetic sample diversity and difficulty during both data inversion and …

Data-free knowledge distillation (D-KD) is able to utilize the knowledge learned by a large teacher network to augment the training of a smaller student network without accessing the original …