114 citations · 299 across the 51 of their papers we have counts for
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Gene Incremental Learning for Single-Cell Transcriptomics
Jiaxin Qi, Yan Cui, Jianqiang Huang +1
Classes, as fundamental elements of Computer Vision, have been extensively studied within incremental learning frameworks. In contrast, tokens, which play essential roles in many r…
Hierarchical Fusion of Local and Global Visual Features with Mixture-of-Experts for Remote Sensing Image Scene Classification
Yuanhao Tang, Xuechao Zou, Zhengpei Hu +3
Remote sensing image scene classification remains a challenging task, primarily due to the complex spatial structures and multi-scale characteristics of ground objects. Although CN…
Graph Neural Networks as a Substitute for Transformers in Single-Cell Transcriptomics
Jiaxin Qi, Yan Cui, Jinli Ou +2
Graph Neural Networks (GNNs) and Transformers share significant similarities in their encoding strategies for interacting with features from nodes of interest, where Transformers u…
A Comprehensive Benchmark for Electrocardiogram Time-Series
Zhijiang Tang, Jiaxin Qi, Yuhua Zheng +1
Electrocardiogram~(ECG), a key bioelectrical time-series signal, is crucial for assessing cardiac health and diagnosing various diseases. Given its time-series format, ECG data is…
Exploring Linear Attention Alternative for Single Image Super-Resolution
Rongchang Lu, Changyu Li, Donghang Li +3
Deep learning-based single-image super-resolution (SISR) technology focuses on enhancing low-resolution (LR) images into high-resolution (HR) ones. Although significant progress ha…