课题基金 / 基金详情

Structured Models for Human Activity Recognition

Structured Models for Human Activity Recognition
人类活动识别的结构化模型
批准号:
RGPIN-2016-05474
负责人:
Mori, Gregory
金额:
$4.41万
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

项目摘要

项目成果

Mori, Gregory的其他基金

相似基金

相关文献

中文摘要
翻译
近年来,计算机视觉领域取得了巨大的进步。在各种识别问题(如物体识别、人类行为识别)上的自动解释的准确性和能力都有了显著提高。这一进步是由新的问题定义和表示、强大的机器学习算法的复兴以及对大量标记训练数据的访问所推动的。
英文摘要
Great strides have been made within computer vision in recent years. Accuracy and capacity for automatic interpretation on a variety of recognition problems -- e.g. object recognition, human action recognition -- have improved dramatically. This progress has been driven by novel problem definitions and representations, the resurgence of powerful machine learning algorithms, and access to large quantities of labeled training data.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Structured Models for Human Activity Recognition
  • 批准号:
    RGPIN-2016-05474
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.41万
  • 财政年份:
    2021
  • 负责人:
    Mori, Gregory
  • 依托单位:
Structured Models for Human Activity Recognition
  • 批准号:
    RGPIN-2016-05474
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.41万
  • 财政年份:
    2020
  • 负责人:
    Mori, Gregory
  • 依托单位:
Structured Models for Human Activity Recognition
  • 批准号:
    RGPIN-2016-05474
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.41万
  • 财政年份:
    2019
  • 负责人:
    Mori, Gregory
  • 依托单位:
Structured Models for Human Activity Recognition
  • 批准号:
    RGPIN-2016-05474
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.41万
  • 财政年份:
    2018
  • 负责人:
    Mori, Gregory
  • 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
新型手性NAD(P)H Models合成及生化模拟