中国矿业大学主页平台系统 Rui Yao--Home-- Efficient dense labelling of human activity sequences from wearables using fully convolutional networks

Home > Scientific Research > Paper Publications

Efficient dense labelling of human activity sequences from wearables using fully convolutional networks

Release time:2021-09-28 Hits:

Affiliation of Author(s):计算机科学与技术学院
Funded by:国家自然科学基金项目
First Author:Rui Yao
Indexed by:Journal paper
Document Code:paper_105731
Volume:2018;78;252–266
ISSN No.:0031-3203
Translation or Not:no
Date of Publication:2018-02-10

Pre One:Real-Time Visual Tracking with Compact Shape and Color Feature

Next One:Part-Based Robust Tracking Using Online Latent Structured Learning

Home

Scientific Research

Teaching Research

Awards and Honours

Enrollment Information

Student Information

My Album

Blog

Personal Information

Other Contact Information

Efficient dense labelling of human activity sequences from wearables using fully convolutional networks