Zobrazeno 1 - 10
of 11 442
pro vyhledávání: '"P, Radha"'
Autor:
Kumar, C. Senthil, Radha, R.
Publikováno v:
Wave motion 133 (2025) 103456
In this paper, we analyse the (3+1) dimensional Bogoyavlensky - Konopelchenko equation. Using Painlev\'e Truncation approach, we have constructed solutions in terms of lower dimensional arbitrary functions of space and time. By suitably harnessing th
Externí odkaz:
http://arxiv.org/abs/2412.10333
Autor:
Lu, Xiaohu, Radha, Hayder
Object detection using LiDAR point clouds relies on a large amount of human-annotated samples when training the underlying detectors' deep neural networks. However, generating 3D bounding box annotation for a large-scale dataset could be costly and t
Externí odkaz:
http://arxiv.org/abs/2412.08806
Attestation of documents like legal papers, professional qualifications, medical records, and commercial documents is crucial in global transactions, ensuring their authenticity, integrity, and trustworthiness. Companies expanding operations internat
Externí odkaz:
http://arxiv.org/abs/2412.01531
This paper considers the problem of designing non-pharmaceutical intervention (NPI) strategies, such as masking and social distancing, to slow the spread of a viral epidemic. We formulate the problem of jointly minimizing the infection probabilities
Externí odkaz:
http://arxiv.org/abs/2411.18982
Instruction tuning has been widely adopted to ensure large language models (LLMs) follow user instructions effectively. The resulting instruction-following capabilities of LLMs heavily rely on the instruction datasets used for tuning. Recently, synth
Externí odkaz:
http://arxiv.org/abs/2411.07133
Random Access is a critical procedure using which a User Equipment (UE) identifies itself to a Base Station (BS). Random Access starts with the UE transmitting a random preamble on the Physical Random Access Channel (PRACH). In a conventional BS rece
Externí odkaz:
http://arxiv.org/abs/2411.08919
Autor:
Zhou, Ce, Yan, Qiben, Kent, Daniel, Wang, Guangjing, Ding, Weikang, Zhang, Ziqi, Radha, Hayder
Monocular Depth Estimation (MDE) is a pivotal component of vision-based Autonomous Driving (AD) systems, enabling vehicles to estimate the depth of surrounding objects using a single camera image. This estimation guides essential driving decisions, s
Externí odkaz:
http://arxiv.org/abs/2411.00192
The spin-valley or Kramers qubit promises significantly enhanced spin-valley lifetimes due to strong coupling of the electrons' spin to their momentum (valley) degrees of freedom. In transition metal dichalcogenides (TMDCs) such spin-valley locking i
Externí odkaz:
http://arxiv.org/abs/2410.21814
Autor:
Niu, Luyao, Zhang, Hongchao, Sahabandu, Dinuka, Ramasubramanian, Bhaskar, Clark, Andrew, Poovendran, Radha
Multi-agent cyber-physical systems are present in a variety of applications. Agent decision-making can be affected due to errors induced by uncertain, dynamic operating environments or due to incorrect actions taken by an agent. When an erroneous dec
Externí odkaz:
http://arxiv.org/abs/2410.20288
Accurate localization in indoor environments is a challenge due to the Non Line of Sight (NLoS) nature of the signaling. In this paper, we explore the use of AI/ML techniques for positioning accuracy enhancement in Indoor Factory (InF) scenarios. The
Externí odkaz:
http://arxiv.org/abs/2410.19436