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

Methods of Classification and Identification01:28

Methods of Classification and Identification

1.6K
Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
1.6K
Chromatographic Methods: Classification01:12

Chromatographic Methods: Classification

4.4K
Chromatographic techniques are classified in three ways: the classification is based on the physical state of the stationary and mobile phases, how the mobile phase and the stationary phase contact each other, or through the chemical or physical processes that isolate the components of the sample. Typically, the mobile phase is either a liquid or gas, while the stationary phase is either a solid or a liquid layer applied to a solid surface.
Chromatographic techniques are typically named by...
4.4K
Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

1.5K
Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...
1.5K
Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

2.0K
Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
2.0K

You might also read

Related Articles

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

Sort by
Same author

Improved technique for retrieval of forest parameters from hyperspectral remote sensing data.

Optics express·2015
Same author

Retrieval of forest stand attributes using optical airborne remote sensing data.

Optics express·2014
Same author

Parameterization of light absorption by components of seawater in optically complex coastal waters of the Crimea Peninsula (Black Sea).

Applied optics·2009
See all related articles

Related Experiment Video

Updated: Mar 18, 2026

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

2.9K

Testing different classification methods in airborne hyperspectral imagery processing.

Vladimir V Kozoderov, Egor V Dmitriev

    Optics Express
    |July 14, 2016
    PubMed
    Summary

    This study compares supervised classification methods for optical remote sensing imagery, evaluating land surface object pattern recognition to improve machine learning efficiency.

    Area of Science:

    • Earth Observation
    • Computer Science

    Background:

    • Optical remote sensing imagery processing relies on machine learning algorithms.
    • Efficient land surface object pattern recognition is crucial for accurate analysis.

    Purpose of the Study:

    • To enhance machine learning algorithm efficiency in optical remote sensing.
    • To compare various supervised classification techniques for land surface object recognition.

    Main Methods:

    • Evaluated metrical classifiers using Euclidean distance.
    • Assessed K-nearest neighbors (KNN) classifiers via majority vote.
    • Analyzed Bayesian classifiers for statistical decision-making.
    • Examined Support Vector Machine (SVM) classifiers for optimization problems.

    More Related Videos

    Identification of Metal Oxide Nanoparticles in Histological Samples by Enhanced Darkfield Microscopy and Hyperspectral Mapping
    12:19

    Identification of Metal Oxide Nanoparticles in Histological Samples by Enhanced Darkfield Microscopy and Hyperspectral Mapping

    Published on: December 8, 2015

    13.0K
    Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
    07:34

    Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

    Published on: August 22, 2019

    8.5K

    Related Experiment Videos

    Last Updated: Mar 18, 2026

    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
    07:05

    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

    Published on: June 18, 2021

    2.9K
    Identification of Metal Oxide Nanoparticles in Histological Samples by Enhanced Darkfield Microscopy and Hyperspectral Mapping
    12:19

    Identification of Metal Oxide Nanoparticles in Histological Samples by Enhanced Darkfield Microscopy and Hyperspectral Mapping

    Published on: December 8, 2015

    13.0K
    Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
    07:34

    Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

    Published on: August 22, 2019

    8.5K

    Main Results:

    • Detailed descriptions of techniques applied to test regions.
    • Comparative analysis of listed classifiers' performance.
    • Identification of optimal classifiers for specific remote sensing tasks.

    Conclusions:

    • The study provides a comparative framework for selecting appropriate classifiers.
    • Findings contribute to improving the accuracy and efficiency of remote sensing data analysis.