Zobrazeno 1 - 10
of 646
pro vyhledávání: '"Lin Hongwei"'
LiDAR-based outdoor 3D object detection has received widespread attention. However, training 3D detectors from the LiDAR point cloud typically relies on expensive bounding box annotations. This paper presents OC3D, an innovative weakly supervised met
Externí odkaz:
http://arxiv.org/abs/2408.08092
Quantum signal processing and quantum singular value transformation are powerful tools to implement polynomial transformations of block-encoded matrices on quantum computers, and has achieved asymptotically optimal complexity in many prominent quantu
Externí odkaz:
http://arxiv.org/abs/2408.01439
Porous structures are materials consisting of minuscule pores, where the microstructure morphology significantly impacts their macroscopic properties. Integrating different porous structures through a blending method is indispensable to cater to dive
Externí odkaz:
http://arxiv.org/abs/2405.20580
Widely employed in cognitive psychology, Gestalt theory elucidates basic principles in visual perception, but meanwhile presents significant challenges for computation. The advancement of artificial intelligence requires the emulation of human cognit
Externí odkaz:
http://arxiv.org/abs/2405.20583
Autor:
Chen, Yu, Lin, Hongwei
The extraction of singular patterns is a fundamental problem in theoretical and practical domains due to the ability of such patterns to detect the intrinsic characteristics of vector fields. In this study, we propose an approach for extracting singu
Externí odkaz:
http://arxiv.org/abs/2404.01007
Autor:
Lu, Xi, Lin, Hongwei
We first show that the standard deviation error of quantum amplitude estimation is asymptotically lower bounded by approximately $1.28 L^{-1}$, where $L$ is the number of queries. Then we propose a generalized qubitization that can block-encode sever
Externí odkaz:
http://arxiv.org/abs/2306.16695
Autor:
Lu, Xi, Lin, Hongwei
The maximum likelihood amplitude estimation algorithm (MLAE) is a practical solution to the quantum amplitude estimation problem with Heisenberg limit error convergence. We improve MLAE by using random depths to avoid the so-called critical points, a
Externí odkaz:
http://arxiv.org/abs/2301.00528
Autor:
Yan, Jiacong, Lin, Hongwei
Porous structures are widely used in various industries because of their excellent properties. Porous surfaces have no thickness and should be thickened to sheet structures for further fabrication. However, conventional methods for generating sheet s
Externí odkaz:
http://arxiv.org/abs/2212.10185
Autor:
Jiang, Yini, Lin, Hongwei
The fairing curves and surfaces are used extensively in geometric design, modeling, and industrial manufacturing. However, the majority of conventional fairing approaches, which lack sufficient parameters to improve fairness, are based on energy mini
Externí odkaz:
http://arxiv.org/abs/2211.11416
Autor:
Lu, Xi, Lin, Hongwei
Quantum phase estimation algorithm (PEA) is one of the most important algorithms in early studies of quantum computation. It is also a key for many other quantum algorithms, such as the quantum counting algorithm and the Shor's integer factorization
Externí odkaz:
http://arxiv.org/abs/2210.00231