Zobrazeno 1 - 10
of 8 872
pro vyhledávání: '"Paull A"'
Autor:
Mokhtarian, Armin, Xu, Jianye, Scheffe, Patrick, Kloock, Maximilian, Schäfer, Simon, Bang, Heeseung, Le, Viet-Anh, Ulhas, Sangeet, Betz, Johannes, Wilson, Sean, Berman, Spring, Paull, Liam, Prorok, Amanda, Alrifaee, Bassam
Connected and automated vehicles and robot swarms hold transformative potential for enhancing safety, efficiency, and sustainability in the transportation and manufacturing sectors. Extensive testing and validation of these technologies is crucial fo
Externí odkaz:
http://arxiv.org/abs/2408.14199
Bayesian estimation is a vital tool in robotics as it allows systems to update the belief of the robot state using incomplete information from noisy sensors. To render the state estimation problem tractable, many systems assume that the motion and me
Externí odkaz:
http://arxiv.org/abs/2408.00907
Autor:
Paull Andrews Carvalho dos Santos, Michelle de Oliveira Maia Parente, Henrique Nunes Parente, Anderson de Moura Zanine, Miguel Arcanjo Moreira Filho, Arnaud Azevêdo Alves, Daniele de Jesus Ferreira, Ruan Mourão da Silva Gomes, Viviany Lúcia Fernandes dos Santos
Publikováno v:
Italian Journal of Animal Science, Vol 18, Iss 1, Pp 236-245 (2019)
Twenty crossbred lambs (21.6 ± 3.5 kg BW) were used in a completely randomised design to determine the effects of babassu mesocarp flour (BMF) on performance and ingestive behaviour. The treatments were defined by the increase in concentrations (0,
Externí odkaz:
https://doaj.org/article/af89f4e24e25412bb45bbf3916b4e1e1
Semantic segmentation plays a crucial role in enabling comprehensive scene understanding for robotic systems. However, generating annotations is challenging, requiring labels for every pixel in an image. In scenarios like autonomous driving, there's
Externí odkaz:
http://arxiv.org/abs/2404.13148
Teacher-Student Curriculum Learning (TSCL) is a curriculum learning framework that draws inspiration from human cultural transmission and learning. It involves a teacher algorithm shaping the learning process of a learner algorithm by exposing it to
Externí odkaz:
http://arxiv.org/abs/2404.03084
Autor:
Rowe, Luke, Girgis, Roger, Gosselin, Anthony, Carrez, Bruno, Golemo, Florian, Heide, Felix, Paull, Liam, Pal, Christopher
Evaluating autonomous vehicle stacks (AVs) in simulation typically involves replaying driving logs from real-world recorded traffic. However, agents replayed from offline data are not reactive and hard to intuitively control. Existing approaches addr
Externí odkaz:
http://arxiv.org/abs/2403.19918
This paper presents an innovative approach to address the challenges of translating multi-modal emotion recognition models to a more practical and resource-efficient uni-modal counterpart, specifically focusing on speech-only emotion recognition. Rec
Externí odkaz:
http://arxiv.org/abs/2401.03000
Deep neural networks (DNNs) often fail silently with over-confident predictions on out-of-distribution (OOD) samples, posing risks in real-world deployments. Existing techniques predominantly emphasize either the feature representation space or the g
Externí odkaz:
http://arxiv.org/abs/2312.14427
Autor:
Liu, Zhen, Feng, Yao, Xiu, Yuliang, Liu, Weiyang, Paull, Liam, Black, Michael J., Schölkopf, Bernhard
The creation of photorealistic virtual worlds requires the accurate modeling of 3D surface geometry for a wide range of objects. For this, meshes are appealing since they 1) enable fast physics-based rendering with realistic material and lighting, 2)
Externí odkaz:
http://arxiv.org/abs/2310.15168
Autor:
Gu, Qiao, Kuwajerwala, Alihusein, Morin, Sacha, Jatavallabhula, Krishna Murthy, Sen, Bipasha, Agarwal, Aditya, Rivera, Corban, Paul, William, Ellis, Kirsty, Chellappa, Rama, Gan, Chuang, de Melo, Celso Miguel, Tenenbaum, Joshua B., Torralba, Antonio, Shkurti, Florian, Paull, Liam
For robots to perform a wide variety of tasks, they require a 3D representation of the world that is semantically rich, yet compact and efficient for task-driven perception and planning. Recent approaches have attempted to leverage features from larg
Externí odkaz:
http://arxiv.org/abs/2309.16650