JoVE
JoVE
Faculty Resource Center
Research
Behavior
Biochemistry
Biology
Bioengineering
Cancer Research
Chemistry
Developmental Biology
Engineering
Environment
Genetics
Immunology and Infection
Medicine
Neuroscience
JoVE Journal
JoVE Encyclopedia of Experiments
JoVE Chrome Extension
Education
Biology
Chemistry
Clinical
Engineering
Environmental Sciences
Pharmacology
Physics
Psychology
Statistics
JoVE Core
JoVE Science Education
JoVE Lab Manual
JoVE Quiz
JoVE Business
Videos Mapped to your Course
Authors
Librarians
High Schools
About
Sign-In
Sign In
Contact Us
Research
JoVE Journal
JoVE Encyclopedia of Experiments
Education
JoVE Core
JoVE Science Education
JoVE Lab Manual
High Schools
EN
EN - English
CN - 中文
DE - Deutsch
ES - Español
KR - 한국어
IT - Italiano
FR - Français
PT - Português
EN
EN - English
CN - 中文
DE - Deutsch
ES - Español
KR - 한국어
IT - Italiano
FR - Français
PT - Português
Close
Research
Behavior
Biochemistry
Bioengineering
Biology
Cancer Research
Chemistry
Developmental Biology
Engineering
Environment
Genetics
Immunology and Infection
Medicine
Neuroscience
Products
JoVE Journal
JoVE Encyclopedia of Experiments
Education
Biology
Chemistry
Clinical
Engineering
Environmental Sciences
Pharmacology
Physics
Psychology
Statistics
Products
JoVE Core
JoVE Science Education
JoVE Lab Manual
JoVE Quiz
JoVE Business
Videos Mapped to Your Course
Teacher Resources
Get in Touch
Instant Trial
Log In
EN
EN - English
CN - 中文
DE - Deutsch
ES - Español
KR - 한국어
IT - Italiano
FR - Français
PT - Português
Journal
/
Behavior
/
用于自动行为分析的深入行为、深度学习工具箱的分步实施
JoVE Journal
Behavior
A subscription to JoVE is required to view this content.
Sign in or start your free trial.
JoVE Journal
Behavior
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
Please note that all translations are automatically generated.
Click here for the English version.
用于自动行为分析的深入行为、深度学习工具箱的分步实施
DOI:
10.3791/60763-v
•
05:41 min
•
February 06, 2020
•
Sanjay Shukla
,
Ahmet Arac
1
Department of Neurology
,
David Geffen School of Medicine, University of California, Los Angeles
Chapters
00:05
Introduction
01:05
Tensor Box
02:26
YOLOv3 and Openpose
03:37
Openpose
03:58
Results: Deepbehavior Toolbox
04:41
Conclusion
Summary
Automatic Translation
English (Original)
العربية (Arabic)
中文 (Chinese)
Nederlands (Dutch)
français (French)
Deutsch (German)
עברית (Hebrew)
italiano (Italian)
日本語 (Japanese)
한국어 (Korean)
português (Portuguese)
русский (Russian)
español (Spanish)
Türkçe (Turkish)
Automatic Translation
该协议的目的是利用预构建的卷积神经网络来自动执行行为跟踪并执行详细的行为分析。行为跟踪可应用于任何视频数据或图像序列,并可通用跟踪任何用户定义的对象。
Tags
Deep Learning
Behavior Analysis
Automated Behavior Quantification
DeepBehavior Toolbox
Tensor Box
Object Detection
Multi-object Tracking
Human Pose Tracking
MATLAB
Convolutional Neural Network
YOLOv3
Object Labeling
Deep Learning Implementation
Article
Embed
ADD TO PLAYLIST
Usage Statistics
Related Videos
背景和线索恐惧制约试验小鼠中使用视频分析系统
社会认知的非人类灵长类动物评估使用电脑自动学习设备(ALDM)测试系统的网络
量化学习婴幼儿:跟踪腿操作期间发现,学习任务
一般方法评估对静脉注射甲基苯丙胺的自我管理深部脑刺激的影响
协议进行数据采集和分析应用到自动人脸表情分析技术和时序分析感官评价
基于线虫人群的化学感应优选测定的自动分析
压力增强恐惧学习--创伤后应激障碍的健壮啮齿动物模型
对比度增强记录 (PrAnCER) 的爪打印分析:用于评估电机缺陷的低成本、开放访问自动步态分析系统
使用移动眼动追踪器捕捉联合视觉注意力的方法
使用功能学习腿分割和跟踪 (FLLIT) 在自由移动昆虫中实现全自动腿部跟踪
Read Article