Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

8.7K
Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
8.7K
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

3.1K
3.1K
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

2.7K
2.7K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

7.4K
Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...
7.4K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

2.6K
2.6K
Vision01:24

Vision

60.0K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
60.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

FMCW Radar-Aided Navigation for Unmanned Aircraft Approach and Landing in AAM Scenarios: System Requirements and Processing Pipeline.

Sensors (Basel, Switzerland)·2025
Same author

Multi-Drone Cooperation for Improved LiDAR-Based Mapping.

Sensors (Basel, Switzerland)·2024
Same author

The Use of Artificial Intelligence Approaches for Performance Improvement of Low-Cost Integrated Navigation Systems.

Sensors (Basel, Switzerland)·2023
Same author

Innovative Fusion Strategy for MEMS Redundant-IMU Exploiting Custom 3D Components.

Sensors (Basel, Switzerland)·2023
Same author

Low-Cost and High-Performance Solution for Positioning and Monitoring of Large Structures.

Sensors (Basel, Switzerland)·2022
Same author

Performance Enhancement of Consumer-Grade MEMS Sensors through Geometrical Redundancy.

Sensors (Basel, Switzerland)·2021

Related Experiment Video

Updated: Feb 4, 2026

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.1K

A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications.

Roberto Opromolla1, Giancarmine Fasano2, Domenico Accardo3

  • 1Department of Industrial Engineering, University of Naples Federico II, Piazzale Tecchio 80, 80125 Naples, Italy. roberto.opromolla@unina.it.

Sensors (Basel, Switzerland)
|October 13, 2018
PubMed
Summary

This study introduces a visual system for Unmanned Aerial Vehicles (UAVs) to autonomously track other aircraft using template matching. The approach enhances navigation in various conditions, including GPS-denied environments.

Keywords:
autonomous navigationcooperative UAV applicationsmorphological filteringtemplate matchingunmanned aerial vehiclesvisual detectionvisual tracking

More Related Videos

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision
09:29

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

Published on: February 11, 2014

13.5K
Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
10:23

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Published on: June 23, 2023

3.5K

Related Experiment Videos

Last Updated: Feb 4, 2026

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.1K
A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision
09:29

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

Published on: February 11, 2014

13.5K
Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
10:23

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Published on: June 23, 2023

3.5K

Area of Science:

  • Robotics and Autonomous Systems
  • Computer Vision
  • Aerospace Engineering

Background:

  • Autonomous navigation for Unmanned Aerial Vehicles (UAVs) is critical for advanced missions.
  • Cooperative sensing enhances situational awareness and navigation capabilities.
  • Robust target detection and tracking are essential for safe UAV operations, especially in challenging environments.

Purpose of the Study:

  • To develop and validate a visual-based autonomous detection and tracking system for UAVs.
  • To enable cooperative navigation using a monocular camera and inter-vehicle communication.
  • To improve UAV navigation performance in both nominal and GPS-challenged scenarios.

Main Methods:

  • Utilized template matching and morphological filtering for robust visual tracking.
  • Integrated navigation hints (relative positioning, attitude) to optimize image processing.
  • Leveraged a reliable inter-vehicle data link for cooperative information exchange.

Main Results:

  • Demonstrated autonomous detection and tracking of cooperative vehicles across a wide range of distances (meters to tens of meters).
  • Achieved robustness against variations in illumination, target scale, and background clutter.
  • Showcased improved computational efficiency and a balanced trade-off between detection accuracy and false alarms.

Conclusions:

  • The proposed visual-based approach is a foundational element for cooperative UAV architectures.
  • This method significantly enhances UAV navigation, particularly in environments with limited or no Global Navigation Satellite System (GNSS) coverage.
  • The system's performance was validated through experimental flight data, confirming its practical applicability.