most citedHiGDA: Hierarchical Graph of Nodes to Learn Local-to-Global Topology for Semi-Supervised Domain Adaptation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV2025

MergeSlide: Continual Model Merging and Task-to-Class Prompt-Aligned Inference for Lifelong Learning on Whole Slide Images

Doanh C. Bui, Ba Hung Ngo, Hoai Luan Pham +3

Lifelong learning on Whole Slide Images (WSIs) aims to train or fine-tune a unified model sequentially on cancer-related tasks, reducing the resources and effort required for data…

quant-ph2025

Transfer-Based Strategies for Multi-Target Quantum Optimization

Vu Tuan Hai, Bui Cao Doanh, Le Vu Trung Duong +2

We address the challenge of multi-target quantum optimization, where the objective is to simultaneously optimize multiple cost functions defined over the same quantum search space.…

cs.CV2025

Welcome New Doctor: Continual Learning with Expert Consultation and Autoregressive Inference for Whole Slide Image Analysis

Doanh Cao Bui, Jin Tae Kwak

Whole Slide Image (WSI) analysis, with its ability to reveal detailed tissue structures in magnified views, plays a crucial role in cancer diagnosis and prognosis. Due to their gig…

cs.CV2025

Lifelong Whole Slide Image Analysis: Online Vision-Language Adaptation and Past-to-Present Gradient Distillation

Doanh C. Bui, Hoai Luan Pham, Vu Trung Duong Le +4

Whole Slide Images (WSIs) play a crucial role in accurate cancer diagnosis and prognosis, as they provide tissue details at the cellular level. However, the rapid growth of computa…

cs.CV2025

ZeroSlide: Is Zero-Shot Classification Adequate for Lifelong Learning in Whole-Slide Image Analysis in the Era of Pathology Vision-Language Foundation Models?

Doanh C. Bui, Hoai Luan Pham, Vu Trung Duong Le +3

Lifelong learning for whole slide images (WSIs) poses the challenge of training a unified model to perform multiple WSI-related tasks, such as cancer subtyping and tumor classifica…

cs.CV20241 cited

HiGDA: Hierarchical Graph of Nodes to Learn Local-to-Global Topology for Semi-Supervised Domain Adaptation

Ba Hung Ngo, Doanh C. Bui, Nhat-Tuong Do-Tran +1

The enhanced representational power and broad applicability of deep learning models have attracted significant interest from the research community in recent years. However, these…