Zobrazeno 1 - 10
of 1 385
pro vyhledávání: '"LIU, Xinran"'
Autor:
Liu, Xinran, Bai, Yikun, Martín, Rocío Díaz, Shi, Kaiwen, Shahbazi, Ashkan, Landman, Bennett A., Chang, Catie, Kolouri, Soheil
Efficient comparison of spherical probability distributions becomes important in fields such as computer vision, geosciences, and medicine. Sliced optimal transport distances, such as spherical and stereographic spherical sliced Wasserstein distances
Externí odkaz:
http://arxiv.org/abs/2411.06055
Ensuring adherence to traffic sign regulations is essential for both human and autonomous vehicle navigation. While current benchmark datasets concentrate on lane perception or basic traffic sign recognition, they often overlook the intricate task of
Externí odkaz:
http://arxiv.org/abs/2410.23780
Autor:
Liu, Xinran, Martín, Rocío Díaz, Bai, Yikun, Shahbazi, Ashkan, Thorpe, Matthew, Aldroubi, Akram, Kolouri, Soheil
The optimal transport (OT) problem has gained significant traction in modern machine learning for its ability to: (1) provide versatile metrics, such as Wasserstein distances and their variants, and (2) determine optimal couplings between probability
Externí odkaz:
http://arxiv.org/abs/2410.12176
High-Definition Maps (HD maps) are essential for the precise navigation and decision-making of autonomous vehicles, yet their creation and upkeep present significant cost and timeliness challenges. The online construction of HD maps using on-board se
Externí odkaz:
http://arxiv.org/abs/2409.05352
Long-term Action Quality Assessment (AQA) evaluates the execution of activities in videos. However, the length presents challenges in fine-grained interpretability, with current AQA methods typically producing a single score by averaging clip feature
Externí odkaz:
http://arxiv.org/abs/2408.11687
Autor:
Maouloud, Sid El Moctar Ahmed, Nguyen, Anh, Liu, XinRan, Dobson, James Edward Young, Ghag, Chamkaur, Floch, Léna Le, Meehan, Emma, Murphy, Alexander St. John, Paling, Sean Michael, Saakyan, Ruben, Scovell, Paul Robert, Toth, Christopher
The Boulby UnderGround Screening (BUGS) facility, located at the Boulby Underground Laboratory, has significantly advanced its material screening capabilities by installing two XIA UltraLo-1800 alpha particle detectors. This study presents a comprehe
Externí odkaz:
http://arxiv.org/abs/2408.06925
Autor:
Peng, Liang, Gao, Junyuan, Liu, Xinran, Li, Weihong, Dong, Shaohua, Zhang, Zhipeng, Fan, Heng, Zhang, Libo
In this paper, we introduce a novel benchmark, dubbed VastTrack, towards facilitating the development of more general visual tracking via encompassing abundant classes and videos. VastTrack possesses several attractive properties: (1) Vast Object Cat
Externí odkaz:
http://arxiv.org/abs/2403.03493
Autor:
Bai, Yikun, Martin, Rocio Diaz, Kothapalli, Abihith, Du, Hengrong, Liu, Xinran, Kolouri, Soheil
The Gromov-Wasserstein (GW) distance has gained increasing interest in the machine learning community in recent years, as it allows for the comparison of measures in different metric spaces. To overcome the limitations imposed by the equal mass requi
Externí odkaz:
http://arxiv.org/abs/2402.03664
Autor:
Tran, Huy, Bai, Yikun, Kothapalli, Abihith, Shahbazi, Ashkan, Liu, Xinran, Martin, Rocio Diaz, Kolouri, Soheil
Comparing spherical probability distributions is of great interest in various fields, including geology, medical domains, computer vision, and deep representation learning. The utility of optimal transport-based distances, such as the Wasserstein dis
Externí odkaz:
http://arxiv.org/abs/2402.02345
Publikováno v:
Frontiers in Public Health, 2023, 11
The COVID-19 infodemic, characterized by the rapid spread of misinformation and unverified claims related to the pandemic, presents a significant challenge. This paper presents a comparative analysis of the COVID-19 infodemic in the English and Chine
Externí odkaz:
http://arxiv.org/abs/2311.08001