From the 2 of 6 linked papers with an AI index.
6 papers
VideoSEMA: a scalable and efficient Mamba-like attention for video understanding
Nhat Thanh Tran, Fanghui Xue andShuai Zhang, Fanghui Xue +5
The paper introduces VideoSEMA, a split space‑time attention model for video classification that combines a scalable Mamba‑like spatial attention block with softmax temporal attent…
SEMA: a Scalable and Efficient Mamba like Attention via Token Localization and Averaging
Nhat Thanh Tran, Fanghui Xue, Shuai Zhang +4
The paper introduces SEMA, a new attention mechanism for vision transformers that combines token localization with arithmetic averaging to avoid the dispersion problem of linear at…
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…
Filter then Attend: Improving attention-based Time Series Forecasting with Spectral Filtering
Elisha Dayag, Nhat Thanh Van Tran, Jack Xin
Transformer-based models are at the forefront in long time-series forecasting (LTSF). While in many cases, these models are able to achieve state of the art results, they suffer fr…