Zobrazeno 1 - 10
of 619
pro vyhledávání: '"Nguyen, Huy‐Hoang"'
Grasp detection is a fundamental robotic task critical to the success of many industrial applications. However, current language-driven models for this task often struggle with cluttered images, lengthy textual descriptions, or slow inference speed.
Externí odkaz:
http://arxiv.org/abs/2409.14403
Mamba, a State Space Model (SSM), has recently shown competitive performance to Convolutional Neural Networks (CNNs) and Transformers in Natural Language Processing and general sequence modeling. Various attempts have been made to adapt Mamba to Comp
Externí odkaz:
http://arxiv.org/abs/2408.14415
Autor:
Nguyen, Huy Hoang, Nguyen, Cuong Nhat, Dao, Xuan Tung, Duong, Quoc Trung, Kim, Dzung Pham Thi, Pham, Minh-Tan
This paper aims to conduct a comparative analysis of contemporary Variational Autoencoder (VAE) architectures employed in anomaly detection, elucidating their performance and behavioral characteristics within this specific task. The architectural con
Externí odkaz:
http://arxiv.org/abs/2408.13561
Osteoarthritis (OA) is the most common musculoskeletal disease, which has no cure. Knee OA (KOA) is one of the highest causes of disability worldwide, and it costs billions of United States dollars to the global community. Prediction of KOA progressi
Externí odkaz:
http://arxiv.org/abs/2408.02349
Combining a vision module inside a closed-loop control system for a \emph{seamless movement} of a robot in a manipulation task is challenging due to the inconsistent update rates between utilized modules. This task is even more difficult in a dynamic
Externí odkaz:
http://arxiv.org/abs/2406.09039
Accurate retinal vessel (RV) segmentation is a crucial step in the quantitative assessment of retinal vasculature, which is needed for the early detection of retinal diseases and other conditions. Numerous studies have been conducted to tackle the pr
Externí odkaz:
http://arxiv.org/abs/2405.16815
One of the primary challenges in brain tumor segmentation arises from the uncertainty of voxels close to tumor boundaries. However, the conventional process of generating ground truth segmentation masks fails to treat such uncertainties properly. Tho
Externí odkaz:
http://arxiv.org/abs/2405.16813
Autor:
Hoang, Thanh Duc, Tung, Do Viet, Nguyen, Duy-Hung, Nguyen, Bao-Sinh, Nguyen, Huy Hoang, Le, Hung
We address catastrophic forgetting issues in graph learning as incoming data transits from one to another graph distribution. Whereas prior studies primarily tackle one setting of graph continual learning such as incremental node classification, we f
Externí odkaz:
http://arxiv.org/abs/2308.13982
Autor:
Kowlagi, Narasimharao, Nguyen, Huy Hoang, McSweeney, Terence, Saarakkala, Simo, määttä, Juhani, Karppinen, Jaro, Tiulpin, Aleksei
This paper addresses the challenge of grading visual features in lumbar spine MRI using Deep Learning. Such a method is essential for the automatic quantification of structural changes in the spine, which is valuable for understanding low back pain.
Externí odkaz:
http://arxiv.org/abs/2210.14597
Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data
Deep neural networks are often applied to medical images to automate the problem of medical diagnosis. However, a more clinically relevant question that practitioners usually face is how to predict the future trajectory of a disease. Current methods
Externí odkaz:
http://arxiv.org/abs/2210.13889