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pro vyhledávání: '"Khang A"'
Autor:
Ta, Calvin-Khang, Dutta, Arindam, Kundu, Rohit, Lal, Rohit, Cruz, Hannah Dela, Raychaudhuri, Dripta S., Roy-Chowdhury, Amit
The Skinned Multi-Person Linear (SMPL) model plays a crucial role in 3D human pose estimation, providing a streamlined yet effective representation of the human body. However, ensuring the validity of SMPL configurations during tasks such as human me
Externí odkaz:
http://arxiv.org/abs/2410.14540
Artificial intelligence aids in brain tumor detection via MRI scans, enhancing the accuracy and reducing the workload of medical professionals. However, in scenarios with extremely limited medical images, traditional deep learning approaches tend to
Externí odkaz:
http://arxiv.org/abs/2410.11307
Publikováno v:
IEEE/RSJ International Conference on Intelligent Robots and Systems 2024
Simultaneous localization and mapping (SLAM) in highly dynamic environments is challenging due to the correlation complexity between moving objects and the camera pose. Many methods have been proposed to deal with this problem; however, the moving pr
Externí odkaz:
http://arxiv.org/abs/2410.12068
Autor:
Blumenthal, Alex, Huynh, Manh Khang
In 1959, Batchelor gave a prediction for the power spectral density of a passive scalar advected by an incompressible fluid exhibiting shear-straining, a mechanism for the creation of small scales in the scalar [Bat59]. Recently, a `cumulative' versi
Externí odkaz:
http://arxiv.org/abs/2410.05473
Autor:
Huynh, Manh Khang
We present a simple construction of an ODE on $\mathbb{R}^{n}$ where the vector field is smooth, and finite-time blow-up is equivalent to the halting problem for a universal Turing machine.
Comment: 1 figure
Comment: 1 figure
Externí odkaz:
http://arxiv.org/abs/2410.01455
Unsupervised pre-training on vast amounts of graph data is critical in real-world applications wherein labeled data is limited, such as molecule properties prediction or materials science. Existing approaches pre-train models for specific graph domai
Externí odkaz:
http://arxiv.org/abs/2409.19117
Autor:
Pang, Khang Ee
The classical no-slip boundary condition of the Navier-Stokes equations fails to describe the spreading motion of a droplet on a substrate due to the missing small-scale physics near the contact line. In this thesis, we introduce a novel regularizati
Externí odkaz:
http://arxiv.org/abs/2409.17187
Autor:
Goswami, Ashish, Tran, Khang
We study a class polynomials obtained from an enumeration of the number of queen paths. In particular, we find the generating function for the diagonal sequence of this table and the zero distribution of a sequence of related polynomials.
Externí odkaz:
http://arxiv.org/abs/2409.17148
Publikováno v:
Elsevier, Neurocomputing Volume 599 (2024) 128111
Artificial intelligence models encounter significant challenges due to their black-box nature, particularly in safety-critical domains such as healthcare, finance, and autonomous vehicles. Explainable Artificial Intelligence (XAI) addresses these cha
Externí odkaz:
http://arxiv.org/abs/2409.00265
Mapping and characterizing magnetic fields in the Rho Ophiuchus-A molecular cloud with SOFIA/HAWC$+$
Autor:
Lê, Ngân, Tram, Le Ngoc, Karska, Agata, Hoang, Thiem, Diep, Pham Ngoc, Hanasz, Michał, Ngoc, Nguyen Bich, Phuong, Nguyen Thi, Menten, Karl M., Wyrowski, Friedrich, Nguyen, Dieu D., Hoang, Thuong Duc, Khang, Nguyen Minh
Publikováno v:
A&A 690, A191 (2024)
(abridged) Together with gravity, turbulence, and stellar feedback, magnetic fields (B-fields) are thought to play a critical role in the evolution of molecular clouds and star formation processes. We aim to map the morphology and measure the strengt
Externí odkaz:
http://arxiv.org/abs/2408.17122