Skip to Main Content Area
  • CPS-VO
    • Contact Support
  • Browse
    • Calendar
    • Announcements
    • Repositories
    • Groups
  • Search
    • Search for Content
    • Search for a Group
    • Search for People
    • Search for a Project
    • Tagcloud
      
 
Not a member?
Click here to register!
Forgot username or password?
 
Home
National Science Foundation

Cyber-Physical Systems Virtual Organization

Read-only archive of site from September 29, 2023.

CPS-VO

tracking algorithm

biblio

Visible to the public Jointly Optimized Target Detection and Tracking Using Compressive Samples

Submitted by aekwall on Mon, 09/14/2020 - 12:30pm
  • compressive samples
  • tracking algorithm
  • sparse signals
  • signal reconstruction
  • Radar tracking
  • radar target detection
  • radar detection
  • joint target detection
  • joint performance metric
  • joint detection and tracking
  • joint decision and estimation
  • joint CSP Bayesian approach
  • high-resolution radar signals
  • CSP-JDT
  • Detectors
  • radar resolution
  • signal sampling
  • compressive sampling
  • compressed sensing
  • object detection
  • estimation
  • target tracking
  • privacy
  • composability
  • pubcrawl
  • Resiliency
  • cyber-physical systems
  • Bayes methods
biblio

Visible to the public Human Detection and Tracking on Surveillance Video Footage Using Convolutional Neural Networks

Submitted by grigby1 on Fri, 07/03/2020 - 1:15pm
  • object detection
  • video surveillance
  • video signal processing
  • tracking algorithms
  • tracking algorithm
  • tracked movement
  • surveillance video footage
  • Surveillance video
  • spatial correlation filter
  • security system
  • Scalability
  • Resiliency
  • resilience
  • pubcrawl
  • convolutional neural nets
  • Metrics
  • learning (artificial intelligence)
  • image recognition
  • image filtering
  • human tracking
  • human position
  • human detection framework
  • human detection
  • human behaviour
  • deep video
  • Deep Learning Convolutional Neural Networks
  • deep learning
  • convolutional neural networks

Terms of Use  |  ©2023. CPS-VO