activity
20242026
most citedMulti-source-free Domain Adaptation via Uncertainty-aware Adaptive Distillation

5 citations · 10 across the 15 of their papers we have counts for

collaborators
Showing 2024Show all

7 papers · 1 filter

cs.CV2024

AMNCutter: Affinity-Attention-Guided Multi-View Normalized Cutter for Unsupervised Surgical Instrument Segmentation

Mingyu Sheng, Jianan Fan, Dongnan Liu +2

Surgical instrument segmentation (SIS) is pivotal for robotic-assisted minimally invasive surgery, assisting surgeons by identifying surgical instruments in endoscopic video frames…

eess.IV2024

Cell as Point: One-Stage Framework for Efficient Cell Tracking

Yaxuan Song, Jianan Fan, Heng Huang +2

Conventional multi-stage cell tracking approaches rely heavily on detection or segmentation in each frame as a prerequisite, requiring substantial resources for high-quality segmen…

cs.CV2024★ 1 cited

Revisiting Surgical Instrument Segmentation Without Human Intervention: A Graph Partitioning View

Mingyu Sheng, Jianan Fan, Dongnan Liu +2

Surgical instrument segmentation (SIS) on endoscopic images stands as a long-standing and essential task in the context of computer-assisted interventions for boosting minimally in…

q-bio.QM2024★ 1 cited

Revisiting Adaptive Cellular Recognition Under Domain Shifts: A Contextual Correspondence View

Jianan Fan, Dongnan Liu, Canran Li +5

Cellular nuclei recognition serves as a fundamental and essential step in the workflow of digital pathology. However, with disparate source organs and staining procedures among his…

cs.LG2024

Seeing Unseen: Discover Novel Biomedical Concepts via Geometry-Constrained Probabilistic Modeling

Jianan Fan, Dongnan Liu, Hang Chang +3

Machine learning holds tremendous promise for transforming the fundamental practice of scientific discovery by virtue of its data-driven nature. With the ever-increasing stream of…

cs.CV2024★ 5 cited

Multi-source-free Domain Adaptation via Uncertainty-aware Adaptive Distillation

Yaxuan Song, Jianan Fan, Dongnan Liu +1

Source-free domain adaptation (SFDA) alleviates the domain discrepancy among data obtained from domains without accessing the data for the awareness of data privacy. However, exist…

cs.CV2024

Learning to Generalize over Subpartitions for Heterogeneity-aware Domain Adaptive Nuclei Segmentation

Jianan Fan, Dongnan Liu, Hang Chang +1

Annotation scarcity and cross-modality/stain data distribution shifts are two major obstacles hindering the application of deep learning models for nuclei analysis, which holds a b…