2 citations · 3 across the 7 of their papers we have counts for
7 papers
VideoSEMA: a scalable and efficient Mamba-like attention for video understanding
Nhat Thanh Tran, Fanghui Xue, Shuai Zhang +4
We present for video understanding (classification) a split space-time attention model, VideoSEMA, consisting of a scalable and efficient Mamba-like attention (SEMA) block in space…
USEMA: a Scalable Efficient Mamba Like Attention for Medical Image Segmentation
Elisha Dayag, Nhat Thanh Tran, Jack Xin
Accurate medical image segmentation is an integral part of the medical image analysis pipeline that requires the ability to merge local and global information. While vision transfo…
Deep Image Prior with L0 Gradient Regularizer for Image Smoothing
Nhat Thanh Tran, Kevin Bui, Jack Xin
Image smoothing is a fundamental image processing operation that preserves the underlying structure, such as strong edges and contours, and removes minor details and textures in an…
CrossLag: Predicting Major Dengue Outbreaks with a Domain Knowledge Informed Transformer
Ashwin Prabu, Nhat Thanh Tran, Guofa Zhou +1
A variety of models have been developed to forecast dengue cases to date. However, it remains a challenge to predict major dengue outbreaks that need timely public warnings the mos…
SEMA: a Scalable and Efficient Mamba like Attention via Token Localization and Averaging
Nhat Thanh Tran, Fanghui Xue, Shuai Zhang +4
Attention is the critical component of a transformer. Yet the quadratic computational complexity of vanilla full attention in the input size and the inability of its linear attenti…
FWin transformer for dengue prediction under climate and ocean influence
Nhat Thanh Tran, Jack Xin, Guofa Zhou
Dengue fever is one of the most deadly mosquito-born tropical infectious diseases. Detailed long range forecast model is vital in controlling the spread of disease and making mitig…
Fourier-Mixed Window Attention: Accelerating Informer for Long Sequence Time-Series Forecasting
Nhat Thanh Tran, Jack Xin
We study a fast local-global window-based attention method to accelerate Informer for long sequence time-series forecasting. While window attention being local is a considerable co…