6 papers
Native Multi-Dimensional Subquadratic Operators via Input Dependent Long Convolutions
David R. Wessels, Farhad Ramezanghorbani, David W. Romero +9
Subquadratic alternatives to attention require compromises when applied to multi-dimensional data: standard convolutions lack global receptive fields and input dependency, while re…
Adaptive extended Kalman filter and laser link acquisition in the detection of gravitational waves in space
Jinke Yang, Yong Xie, Yidi Fan +8
An alternative, new laser link acquisition scheme for the triangular constellation of spacecraft (SCs) in deep space in the detection of gravitational waves is considered. In place…
Fine-grained Multi-class Nuclei Segmentation with Molecular-empowered All-in-SAM Model
Xueyuan Li, Can Cui, Ruining Deng +7
Purpose: Recent developments in computational pathology have been driven by advances in Vision Foundation Models, particularly the Segment Anything Model (SAM). This model facilita…
Img2ST-Net: Efficient High-Resolution Spatial Omics Prediction from Whole Slide Histology Images via Fully Convolutional Image-to-Image Learning
Junchao Zhu, Ruining Deng, Junlin Guo +10
Recent advances in multi-modal AI have demonstrated promising potential for generating the currently expensive spatial transcriptomics (ST) data directly from routine histology ima…
IRS: Incremental Relationship-guided Segmentation for Digital Pathology
Ruining Deng, Junchao Zhu, Juming Xiong +14
Continual learning is rapidly emerging as a key focus in computer vision, aiming to develop AI systems capable of continuous improvement, thereby enhancing their value and practica…
MagNet: Multi-Level Attention Graph Network for Predicting High-Resolution Spatial Transcriptomics
Junchao Zhu, Ruining Deng, Tianyuan Yao +12
The rapid development of spatial transcriptomics (ST) offers new opportunities to explore the gene expression patterns within the spatial microenvironment. Current research integra…