3 citations · 6 across the 14 of their papers we have counts for
19 papers
Benchmarking Data-Free Continual Model Merging for Whole-Slide Image Survival Analysis
Vu Minh Tran, Doanh C. Bui, Maï K. Nguyen +1
Continual survival analysis on whole-slide images (WSIs) requires models to integrate knowledge from sequentially arriving cancer cohorts while preserving previously learned inform…
ICGF-CXRMate: Image-Conditioned Clinical Context Compression and Gated Fusion for Chest X-ray Report Generation
Vu Minh Tran, Thuc Huynh, Son Thanh Luu +1
Auxiliary patient data can improve chest X-ray report generation, but directly concatenating heterogeneous clinical information with visual tokens produces long, variable-length de…
CG-GLORE: A Conjugate Gradient-Based Global-Local Regularization Network for Sparse-View CT Reconstruction
Tran Xuan Hieu Le, Doanh C. Bui, Vu Trung Duong Le +5
Sparse-view computed tomography (CT) reduces radiation dose by acquiring fewer projection views, but the resulting inverse problem is highly ill-posed and often produces severe str…
CGRL: Concept-Guided Pruning and Representation Learning for Whole-Slide Image Classification
Thuc Huynh, Tuan Le, Doanh C. Bui
Weakly supervised whole-slide image (WSI) classification is widely used in computational pathology because slide-level labels are easier to obtain than dense region annotations. Ex…
Toward Efficient Weakly Supervised Semantic Segmentation Using Only Low-Magnification Histopathological Images
Dung Minh Do, Nhat-Thanh Huynh, Duc Minh Huynh +2
Whole-slide images (WSIs) provide rich tissue-level and cellular-level information, but storing and transmitting high-magnification pathology data is resource-intensive. Moreover,…
Continual Model Merging with Test-Time Adaptation for Whole-Slide Image Analysis
Duc-Thanh Le, Doanh C. Bui, Maï K. Nguyen +1
Model merging offers a practical alternative to conventional continual learning by integrating independently fine-tuned models without retaining previous training data. Recent stat…
MergeSurv: Merging-Based Continual Learning for Survival Analysis on Whole-Slide Images
Vu Minh Tran, Doanh C. Bui, Van-Hau Pham +2
Survival analysis on Whole Slide Images (WSIs) is important in computational pathology for prognosis estimation and treatment planning. However, existing survival models are typica…
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…
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.…
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…
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…
Qimax: Efficient quantum simulation via GPU-accelerated extended stabilizer formalism
Vu Tuan Hai, Bui Cao Doanh, Le Vu Trung Duong +2
Simulating Clifford and near-Clifford circuits using the extended stabilizer formalism has become increasingly popular, particularly in quantum error correction. Compared to the st…
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…
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…
MECFormer: Multi-task Whole Slide Image Classification with Expert Consultation Network
Doanh C. Bui, Jin Tae Kwak
Whole slide image (WSI) classification is a crucial problem for cancer diagnostics in clinics and hospitals. A WSI, acquired at gigapixel size, is commonly tiled into patches and p…
QuIIL at T3 challenge: Towards Automation in Life-Saving Intervention Procedures from First-Person View
Trinh T. L. Vuong, Doanh C. Bui, Jin Tae Kwak
In this paper, we present our solutions for a spectrum of automation tasks in life-saving intervention procedures within the Trauma THOMPSON (T3) Challenge, encompassing action rec…
FALFormer: Feature-aware Landmarks self-attention for Whole-slide Image Classification
Doanh C. Bui, Trinh Thi Le Vuong, Jin Tae Kwak
Slide-level classification for whole-slide images (WSIs) has been widely recognized as a crucial problem in digital and computational pathology. Current approaches commonly conside…
CLEAR: Cross-Transformers with Pre-trained Language Model is All you need for Person Attribute Recognition and Retrieval
Doanh C. Bui, Thinh V. Le, Ba Hung Ngo +1
Person attribute recognition and attribute-based retrieval are two core human-centric tasks. In the recognition task, the challenge is specifying attributes depending on a person's…
UIT-OpenViIC: A Novel Benchmark for Evaluating Image Captioning in Vietnamese
Doanh C. Bui, Nghia Hieu Nguyen, Khang Nguyen
Image Captioning is one of the vision-language tasks that still interest the research community worldwide in the 2020s. MS-COCO Caption benchmark is commonly used to evaluate the p…