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

Detection of Black Holes01:10

Detection of Black Holes

2.5K
Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
Not until the 1960s, when the first neutron...
2.5K
Deconvolution01:20

Deconvolution

516
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
516

You might also read

Related Articles

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

Sort by
Same author

Mitochondrial-Targeted SS-31 Attenuates the Doxorubicin-Induced Cardiomyoblast H9C2 Cell Senescence.

Biology·2026
Same author

Process and Mechanism of Nanocarrier-Loaded dsRNA Penetrating the Insect Cuticle: Theoretical Foundation for Transdermal Delivery.

Journal of agricultural and food chemistry·2026
Same author

ALTCCO: an enhanced cuckoo catfish optimizer with LightTrack strategy for engineering design and UAV trajectory optimization.

Scientific reports·2026
Same author

A GA<sub>3</sub>-loaded hydrophilic-lipophilic diblock polymer acts as a nano-safener to alleviate herbicide-induced injury in rice by activating key metabolic pathways.

Plant communications·2026
Same author

An AI-Driven Multimodal Sensing Framework Integrating UAV Imagery and Environmental Sensors for Intelligent Farmland Monitoring.

Sensors (Basel, Switzerland)·2026
Same author

m<sup>6</sup>A-modified Mid1 promotes sevoflurane-induced cognitive impairment in neonatal mice by ubiquitin-mediated degradation of Syngap1.

Experimental & molecular medicine·2026

Related Experiment Video

Updated: Jan 3, 2026

High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning
09:31

High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning

Published on: April 28, 2022

3.4K

Superhigh-Resolution Recognition of Optical Vortex Modes Assisted by a Deep-Learning Method.

Zhanwei Liu1, Shuo Yan1, Haigang Liu1

  • 1State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240, China.

Physical Review Letters
|November 26, 2019
PubMed
Summary

A new deep learning method precisely recognizes orbital angular momentum (OAM) modes with fractional topological charges, achieving unprecedented resolution for optical communication systems.

More Related Videos

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.6K
Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT
12:22

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT

Published on: August 4, 2018

8.9K

Related Experiment Videos

Last Updated: Jan 3, 2026

High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning
09:31

High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning

Published on: April 28, 2022

3.4K
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.6K
Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT
12:22

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT

Published on: August 4, 2018

8.9K

Area of Science:

  • Optical Communications
  • Artificial Intelligence
  • Signal Processing

Background:

  • Orbital angular momentum (OAM) offers theoretical infinite capacity increase in optical communication.
  • Precise recognition of OAM modes is critical for enhancing communication capacity.
  • Current methods face limitations in resolving closely spaced OAM modes.

Purpose of the Study:

  • To propose a novel deep learning (DL) method for precise recognition of OAM modes.
  • To achieve superhigh resolution in distinguishing OAM modes with fractional topological charges.
  • To demonstrate the practical application of this method in an optical communication system.

Main Methods:

  • Development of a deep learning model, specifically convolutional neural networks (CNNs).
  • Training the DL model with extensive datasets to recognize OAM modes.
  • Implementation of a superhigh-resolution OAM multiplexing system for data transfer.

Main Results:

  • Achieved a minimum recognized interval of 0.01 between adjacent OAM modes, a record resolution.
  • Successfully demonstrated the transfer of an image (Einstein portrait) using the OAM multiplexing system.
  • The DL approach shows potential for handling large data volumes for training.

Conclusions:

  • The proposed DL method significantly enhances the resolution for OAM mode recognition.
  • This breakthrough paves the way for next-generation ultrafine OAM optical communication.
  • The method shows potential for generalization to other OAM communication systems (microwave, millimeter wave, terahertz).