Zobrazeno 1 - 10
of 5 773
pro vyhledávání: '"A P, Phuc"'
Generative models hold great potential, but only if one can trust the evaluation of the data they generate. We show that many commonly used quality scores for comparing two-dimensional distributions of synthetic vs. ground-truth data give better resu
Externí odkaz:
http://arxiv.org/abs/2501.00664
We analyze the Susceptible-Infected-Recovered-Susceptible (SIRS) process, a continuous-time Markov chain frequently employed in epidemiology to model the spread of infections on networks. In this framework, infections spread as infected vertices reco
Externí odkaz:
http://arxiv.org/abs/2412.21138
Efficient text retrieval is critical for applications such as legal document analysis, particularly in specialized contexts like Japanese legal systems. Existing retrieval methods often underperform in such domain-specific scenarios, necessitating ta
Externí odkaz:
http://arxiv.org/abs/2412.19265
DC motors have been widely used in many industrial applications, from small jointed robots with multiple degrees of freedom to household appliances and transportation vehicles such as electric cars and trains. The main function of these motors is to
Externí odkaz:
http://arxiv.org/abs/2501.01438
Autor:
Nguyen, Phuc D. A.
Oriented object detection in aerial images poses a significant challenge due to their varying sizes and orientations. Current state-of-the-art detectors typically rely on either two-stage or one-stage approaches, often employing Anchor-based strategi
Externí odkaz:
http://arxiv.org/abs/2412.14379
Autor:
Casparsen, Andreas, Bui, Van-Phuc, Pandey, Shashi Raj, Nielsen, Jimmy Jessen, Popovski, Petar
Video streaming services depend on the underlying communication infrastructure and available network resources to offer ultra-low latency, high-quality content delivery. Open Radio Access Network (ORAN) provides a dynamic, programmable, and flexible
Externí odkaz:
http://arxiv.org/abs/2412.12751
This paper addresses key challenges in object-centric representation learning of video. While existing approaches struggle with complex scenes, we propose a novel weakly-supervised framework that emphasises geometric understanding and leverages pre-t
Externí odkaz:
http://arxiv.org/abs/2412.12331
The immense volume of data generated by Earth observation (EO) satellites presents significant challenges in transmitting it to Earth over rate-limited satellite-to-ground communication links. This paper presents an efficient downlink framework for m
Externí odkaz:
http://arxiv.org/abs/2412.11857
Autor:
Qiu, Peijie, Chakrabarty, Satrajit, Nguyen, Phuc, Ghosh, Soumyendu Sekhar, Sotiras, Aristeidis
Deep learning has made significant strides in automated brain tumor segmentation from magnetic resonance imaging (MRI) scans in recent years. However, the reliability of these tools is hampered by the presence of poor-quality segmentation outliers, p
Externí odkaz:
http://arxiv.org/abs/2412.07156
Autor:
Trung, Quang Hoang, Phuc, Nguyen Van Hoang, Hoang, Le Trung, Hieu, Quang Huu, Duy, Vo Nguyen Le
Text Retrieval (TR) involves finding and retrieving text-based content relevant to a user's query from a large repository, with applications in real-world scenarios such as legal document retrieval. While most existing studies focus on English, limit
Externí odkaz:
http://arxiv.org/abs/2412.13205