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

Association Areas of the Cortex01:21

Association Areas of the Cortex

9.5K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
9.5K
Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.6K
Protein Networks02:26

Protein Networks

2.9K
No description available
2.9K
Network Covalent Solids02:18

Network Covalent Solids

16.2K
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
16.2K
Associative Learning01:27

Associative Learning

1.4K
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
1.4K
Neural Regulation01:37

Neural Regulation

43.5K
Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
43.5K

You might also read

Related Articles

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

Sort by
Same author

Cationic porphyrin-mediated photodynamic inactivation of Candida biofilms and the effect of miconazole.

Journal of physiology and pharmacology : an official journal of the Polish Physiological Society·2016
Same author

Obesity prevention in defined (high school) populations.

International journal of obesity supplements·2014
Same author

Nonlinear optical hit-miss transform for detection.

Applied optics·2010
Same author

High-capacity neural networks on nonideal hardware.

Applied optics·2010
Same author

Morphological and wavelet transforms for object detection and image processing.

Applied optics·2010
Same author

Multitarget-tracking optical processing system.

Applied optics·2010
Same journal

Multifunctional reconfigurable terahertz metasurface based on vanadium dioxide phase transition: achieving broadband absorption and efficient polarization conversion.

Applied optics·2026
Same journal

High-Q-factor electromagnetically induced transparency utilizing quasi-bound states in the continuum in an all-dielectric terahertz metasurface.

Applied optics·2026
Same journal

Automated stitching interferometry for high-precision metrology of X-ray mirrors.

Applied optics·2026
Same journal

Experimental demonstration of an approach to designing a metal-dielectric DBR resonant cavity structure.

Applied optics·2026
Same journal

High-precision wavefront reconstruction from a single-shot interferogram using a physics-driven hybrid feature calibration network.

Applied optics·2026
Same journal

Ultra-high-Q Fano resonance based on coupled topological corner states in Kagome photonic crystals.

Applied optics·2026
See all related articles

Related Experiment Video

Updated: Feb 9, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.1K

Multitarget data association using an optical neural network.

M Yee, D Casasent

    Applied Optics
    |August 20, 2010
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a neural network for multitarget tracking using position and velocity data. The developed network effectively handles noisy data and is suitable for optical implementation.

    More Related Videos

    Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
    07:11

    Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

    Published on: November 10, 2023

    3.3K
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    10.0K

    Related Experiment Videos

    Last Updated: Feb 9, 2026

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    1.1K
    Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
    07:11

    Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

    Published on: November 10, 2023

    3.3K
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    10.0K

    Area of Science:

    • Computer Science
    • Artificial Intelligence
    • Signal Processing

    Background:

    • Multitarget tracking is crucial for various applications, but data association remains a challenge.
    • Existing methods often struggle with noisy measurements and complex scenarios.
    • Optical processing offers potential for high-speed, low-power implementations.

    Purpose of the Study:

    • To present a novel neural network approach for solving the data association problem in multitarget tracking.
    • To develop a quadratic neural energy function amenable to optical implementation.
    • To evaluate the network's performance under realistic noisy conditions.

    Main Methods:

    • Utilized position and velocity measurements from two consecutive time frames.
    • Formulated a quadratic neural energy function for the data association task.
    • Simulated performance using realistic target trajectories with significant measurement noise and platform jitter.
    • Explored optical neural network architectures, including an all-optical matrix-vector multiplication approach.

    Main Results:

    • The neural network demonstrated robust performance in multitarget tracking even with substantial data corruption.
    • The proposed quadratic energy function is well-suited for optical processing.
    • The network effectively associates target tracks in the presence of noise.

    Conclusions:

    • The presented neural network offers an effective solution for the data association problem in multitarget tracking.
    • The approach is viable for optical implementation, paving the way for efficient hardware solutions.
    • The network's resilience to noise makes it suitable for real-world tracking applications.