Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Nguyen, Duy M. H."'
Autor:
Nguyen, Duy M. H., Diep, Nghiem T., Nguyen, Trung Q., Le, Hoang-Bao, Nguyen, Tai, Nguyen, Tien, Nguyen, TrungTin, Ho, Nhat, Xie, Pengtao, Wattenhofer, Roger, Zhou, James, Sonntag, Daniel, Niepert, Mathias
State-of-the-art medical multi-modal large language models (med-MLLM), like LLaVA-Med or BioMedGPT, leverage instruction-following data in pre-training. However, those models primarily focus on scaling the model size and data volume to boost performa
Externí odkaz:
http://arxiv.org/abs/2410.02615
Autor:
Nguyen, Duy M. H., Le, An T., Nguyen, Trung Q., Diep, Nghiem T., Nguyen, Tai, Duong-Tran, Duy, Peters, Jan, Shen, Li, Niepert, Mathias, Sonntag, Daniel
Prompt learning methods are gaining increasing attention due to their ability to customize large vision-language models to new domains using pre-trained contextual knowledge and minimal training data. However, existing works typically rely on optimiz
Externí odkaz:
http://arxiv.org/abs/2407.04489
Autor:
Le, Hoang H., Nguyen, Duy M. H., Bhatti, Omair Shahzad, Kopacsi, Laszlo, Ngo, Thinh P., Nguyen, Binh T., Barz, Michael, Sonntag, Daniel
Comprehending how humans process visual information in dynamic settings is crucial for psychology and designing user-centered interactions. While mobile eye-tracking systems combining egocentric video and gaze signals can offer valuable insights, man
Externí odkaz:
http://arxiv.org/abs/2406.06239
Autor:
Tran, Hoai-Chau, Nguyen, Duy M. H., Nguyen, Duy M., Nguyen, Trung-Tin, Le, Ngan, Xie, Pengtao, Sonntag, Daniel, Zou, James Y., Nguyen, Binh T., Niepert, Mathias
Increasing the throughput of the Transformer architecture, a foundational component used in numerous state-of-the-art models for vision and language tasks (e.g., GPT, LLaVa), is an important problem in machine learning. One recent and effective strat
Externí odkaz:
http://arxiv.org/abs/2405.16148
Autor:
Nguyen, Duy M. H., Lukashina, Nina, Nguyen, Tai, Le, An T., Nguyen, TrungTin, Ho, Nhat, Peters, Jan, Sonntag, Daniel, Zaverkin, Viktor, Niepert, Mathias
A molecule's 2D representation consists of its atoms, their attributes, and the molecule's covalent bonds. A 3D (geometric) representation of a molecule is called a conformer and consists of its atom types and Cartesian coordinates. Every conformer h
Externí odkaz:
http://arxiv.org/abs/2402.01975
Autor:
Nguyen, Duy M. H., Nguyen, Hoang, Diep, Nghiem T., Pham, Tan N., Cao, Tri, Nguyen, Binh T., Swoboda, Paul, Ho, Nhat, Albarqouni, Shadi, Xie, Pengtao, Sonntag, Daniel, Niepert, Mathias
Obtaining large pre-trained models that can be fine-tuned to new tasks with limited annotated samples has remained an open challenge for medical imaging data. While pre-trained deep networks on ImageNet and vision-language foundation models trained o
Externí odkaz:
http://arxiv.org/abs/2306.11925
Autor:
Tusfiqur, Hasan Md, Nguyen, Duy M. H., Truong, Mai T. N., Nguyen, Triet A., Nguyen, Binh T., Barz, Michael, Profitlich, Hans-Juergen, Than, Ngoc T. T., Le, Ngan, Xie, Pengtao, Sonntag, Daniel
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world, and early DR detection is necessary to prevent vision loss and support an appropriate treatment. In this work, we leverage interactive machine learning and introduce a joint le
Externí odkaz:
http://arxiv.org/abs/2212.14615
Autor:
Nguyen, Duy M. H., Nguyen, Hoang, Truong, Mai T. N., Cao, Tri, Nguyen, Binh T., Ho, Nhat, Swoboda, Paul, Albarqouni, Shadi, Xie, Pengtao, Sonntag, Daniel
Collecting large-scale medical datasets with fully annotated samples for training of deep networks is prohibitively expensive, especially for 3D volume data. Recent breakthroughs in self-supervised learning (SSL) offer the ability to overcome the lac
Externí odkaz:
http://arxiv.org/abs/2212.01893
Multi-Camera Multi-Object Tracking is currently drawing attention in the computer vision field due to its superior performance in real-world applications such as video surveillance in crowded scenes or in wide spaces. In this work, we propose a mathe
Externí odkaz:
http://arxiv.org/abs/2111.11892
Self-Supervised Domain Adaptation for Diabetic Retinopathy Grading using Vessel Image Reconstruction
This paper investigates the problem of domain adaptation for diabetic retinopathy (DR) grading. We learn invariant target-domain features by defining a novel self-supervised task based on retinal vessel image reconstructions, inspired by medical doma
Externí odkaz:
http://arxiv.org/abs/2107.09372