4 citations · 9 across the 5 of their papers we have counts for
5 papers
SkipSNN: Efficiently Classifying Spike Trains with Event-attention
Hang Yin, Yao Su, Liping Liu +3
Spike train classification has recently become an important topic in the machine learning community, where each spike train is a binary event sequence with \emph{temporal-sparsity…
Multi-State Brain Network Discovery
Hang Yin, Yao Su, Xinyue Liu +3
Brain network discovery aims to find nodes and edges from the spatio-temporal signals obtained by neuroimaging data, such as fMRI scans of human brains. Existing methods tend to de…
One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data
Yao Su, Zhentian Qian, Lei Ma +2
Brain extraction, registration and segmentation are indispensable preprocessing steps in neuroimaging studies. The aim is to extract the brain from raw imaging scans (i.e., extract…
ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data
Yao Su, Zhentian Qian, Lifang He +1
Brain extraction and registration are important preprocessing steps in neuroimaging data analysis, where the goal is to extract the brain regions from MRI scans (i.e., extraction s…
ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration
Yao Su, Xin Dai, Lifang He +1
Deformable image registration, i.e., the task of aligning multiple images into one coordinate system by non-linear transformation, serves as an essential preprocessing step for neu…