Context Embedding Based on Bi-LSTM in Semi-Supervised Biomedical Word Sense Disambiguation. - Zhi Li; Fan Yang; Yaoru Luo (IEEE Access, 2019)

Segmentation of Intracellular Structures in Fluorescence Microscopy Images by Fusing Low-Level Features. - Yuanhao Guo; Jiaxing Huang; Yanfeng Zhou; Yaoru Luo; Wenjing Li; Ge Yang 002 (PRCV (3), 2021)

Deep Neural Networks Learn Meta-Structures to Segment Fluorescence Microscopy Images. - Yaoru Luo; Guole Liu; Wenjing Li; Yuanhao Guo; Ge Yang 002 (CoRR, 2021)

Advancing biological super-resolution microscopy through deep learning: a brief review. - Tianjie Yang; Yaoru Luo; Wei Ji; Ge Yang 002 (CoRR, 2021)

Fluorescence Microscopy Image Datasets for Deep Learning Segmentation of Intracellular Orgenelle Networks. - Yaoru Luo; Yuanhao Guo; Wenjing Li; Guole Liu; Ge Yang 002 (IEEE DataPort, 2021)

Deep Neural Networks Learn Meta-Structures from Noisy Labels in Semantic Segmentation. - Yaoru Luo; Guole Liu; Yuanhao Guo; Ge Yang 002 (AAAI, 2022)

3d Particle Picking in Cryo-Electron Tomograms Using Instance Segmentation. - Guole Liu; Yaoru Luo; Ge Yang 002 (ICIP, 2022)

Fluorescence Microscopy Images Segmentation Based on Prototypical Networks with a Few Annotations. - Yuanhao Guo; Yaoru Luo; Wenjing Li; Ge Yang 002 (PRCV (2), 2022)

Elucidating Meta-Structures of Noisy Labels in Semantic Segmentation by Deep Neural Networks. - Yaoru Luo; Guole Liu; Yuanhao Guo; Ge Yang 002 (CoRR, 2022)

ADFA: Attention-Augmented Differentiable Top-K Feature Adaptation for Unsupervised Medical Anomaly Detection. - Yiming Huang; Guole Liu; Yaoru Luo; Ge Yang 002 (ICIP, 2023)

Enhancing Robustness of Deep Networks Against Noisy Labels Based on A Two-Phase Formulation of Their Learning Behavior. - Yaoru Luo; Ge Yang (ICME, 2023)

Representing Topological Self-similarity Using Fractal Feature Maps for Accurate Segmentation of Tubular Structures. - Jiaxing Huang; Yanfeng Zhou; Yaoru Luo; Guole Liu; Heng Guo; Ge Yang 002 (ECCV (30), 2024)