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Deep learning with limited data

Deep learning with limited data
数据有限的深度学习
批准号:
RGPIN-2017-05117
负责人:
Trappenberg, Thomas
金额:
$1.89万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31

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中文摘要
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英文摘要
Deep neural networks is a machine learning technique based on a model of neuron-like elements. The "deep" refers here to networks with many layers that are capable of representing complex functions. Such models have been proven to be extremely valuable as they can learn hierarchical data representations from examples and predict previously unseen data. Such techniques enabled much of the recent progress in computer vision and pattern recognition, and the advancements of deep neural networks was made possible by the availability of large data sets (Big Data), some refinement of algorithms, and the availability of increased computational power with specialized processors such as graphical processing units (GPUs). Companies like Google, Microsoft, Amazon and Facebook, and also numerous smaller engineering firms and market analysis firms are embracing this new technology.
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Deep learning with limited data
  • 批准号:
    RGPIN-2017-05117
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.79万
  • 财政年份:
    2021
  • 负责人:
    Trappenberg, Thomas
  • 依托单位:
Deep learning with limited data
  • 批准号:
    RGPIN-2017-05117
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2020
  • 负责人:
    Trappenberg, Thomas
  • 依托单位:
Deep learning with limited data
  • 批准号:
    RGPIN-2017-05117
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2019
  • 负责人:
    Trappenberg, Thomas
  • 依托单位:
Deep learning with limited data
  • 批准号:
    RGPIN-2017-05117
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2018
  • 负责人:
    Trappenberg, Thomas
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Understanding structural evolution of galaxies with machine learning
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2022
  • 负责人:
    Nicola Rosario Napolitano
  • 依托单位:
煤矿安全人机混合群智感知任务的约束动态多目标Q-learning进化分配
  • 批准号:
    --
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    30万元
  • 批准年份:
    2022
  • 负责人:
    吉建娇
  • 依托单位:
基于领弹失效考量的智能弹药编队短时在线Q-learning协同控制机理
  • 批准号:
    62003314
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    24.0万元
  • 批准年份:
    2020
  • 负责人:
    沈剑
  • 依托单位: