3 citations · 4 across the 4 of their papers we have counts for
4 papers
S^2-KD: Semantic-Spectral Knowledge Distillation Spatiotemporal Forecasting
Wenshuo Wang, Yaomin Shen, Yingjie Tan +1
Spatiotemporal forecasting often relies on computationally intensive models to capture complex dynamics. Knowledge distillation (KD) has emerged as a key technique for creating lig…
Physics-Constrained Diffusion Reconstruction with Posterior Correction for Quantitative and Fast PET Imaging
Yucun Hou, Fenglin Zhan, Chenxi Li +13
Deep learning-based reconstruction of positron emission tomography(PET) data has gained increasing attention in recent years. While these methods achieve fast reconstruction,concer…
An Effective Information Theoretic Framework for Channel Pruning
Yihao Chen, Zefang Wang
Channel pruning is a promising method for accelerating and compressing convolutional neural networks. However, current pruning algorithms still remain unsolved problems that how to…
TinySAM: Pushing the Envelope for Efficient Segment Anything Model
Han Shu, Wenshuo Li, Yehui Tang +5
Recently segment anything model (SAM) has shown powerful segmentation capability and has drawn great attention in computer vision fields. Massive following works have developed var…