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Advances in Level Set and Related Methods: New Technology and Applications

Advances in Level Set and Related Methods: New Technology and Applications
水平集及相关方法的进展:新技术与应用
批准号:
0074735
负责人:
Stanley Osher
金额:
$15.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-08-01 至 2004-07-31

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NSF Proposal: DMS-0074735 "Advances in Level Set and Related Methods: New Technologies and Applications" Principal Investigator: Stanley J. OsherABSTRACTThe level set method devised by Osher and Sethian in 1988 has proven to be phenomenally successful as a numerical and theoretical device for representing and analyzing the motion of curves in R^2 and surfaces in R^3. A level set calculus has been developed, and recent extensions include the ghost fluid method, convolution generated motion, dynamic surface extension, the variational level set approach, and the motion of higher codimensional objects. Recent applications include multiphase fluid dynamics, the island dynamics model for epitaxial growth, level set based interpolation of unorganized points, and fast methods in image restoration. This work was partially supported by our previous NSF grants. The goal of this proposed research is to extend the technology and the range of applications through the following two projects:(1) Convolution generated motion for filaments.(2) Fast algorithms for steady state geometric Hamilton-Jacobi equations and the induced motion of fronts.The level set method is rapidly becoming the method of choice to simulate on the computer a host of important physical, biological, materials science, image processing, computer vision, electromagnetic and other real world problems. In particular areas of nanotechnology will also be impacted. Improvements of the numerical methods used to simulate these phenomena will ultimately be crucial in the design of computer chips, analysis of explosions, recognition of objects and many other areas of modern technology. This proposal addresses further improvements of the level set and related methods.
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Collaborative Research: Algorithms, Theory, and Validation of Deep Graph Learning with Limited Supervision: A Continuous Perspective
  • 批准号:
    2208272
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $28.0万
  • 财政年份:
    2022
  • 负责人:
    Stanley Osher
  • 依托单位:
Algorithms for Threat Detection in Sensor Systems for Analyzing Chemical and Biological Systems Based on Compressive Sensing and L1 Related Optimization
  • 批准号:
    1118971
  • 项目类别:
    Standard Grant
  • 资助金额:
    $119.87万
  • 财政年份:
    2011
  • 负责人:
    Stanley Osher
  • 依托单位:
Collaborative Research: ATD (Algorithms for Threat Detection): Inverse Problems Methods in Chemical Threat Detection
  • 批准号:
    0914561
  • 项目类别:
    Standard Grant
  • 资助金额:
    $29.34万
  • 财政年份:
    2009
  • 负责人:
    Stanley Osher
  • 依托单位:
Nonlocal Variational Processing of Image Albums
  • 批准号:
    0714087
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $0.0万
  • 财政年份:
    2007
  • 负责人:
    Stanley Osher
  • 依托单位:
国内基金
海外基金
粒子level set方法的改进与空间自适应波浪模型并行化研究
  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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  • 负责人:
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  • 依托单位:
基于Level Set方法的三维爆炸与冲击仿真软件开发及其应用
  • 批准号:
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  • 项目类别:
    青年科学基金项目
  • 资助金额:
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  • 批准年份:
    2015
  • 负责人:
    张莉
  • 依托单位:
层级稀疏化的Mid-Level特征空间下高分辨率遥感影像检索方法研究
CPU/GPGPU紧耦合异构多核系统共享Last Level Cache优化研究
  • 批准号:
    61379035
  • 项目类别:
    面上项目
  • 资助金额:
    75.0万元
  • 批准年份:
    2013
  • 负责人:
    楼学庆
  • 依托单位: