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

Compacting Factor test01:22

Compacting Factor test

The compacting factor test is a method used to assess the workability of concrete. It is  especially suitable for concrete mixes containing aggregates up to one and a half inches in size. This test involves specialized equipment consisting of two truncated cone-shaped hoppers and a cylinder, all with polished interior surfaces to minimize friction.
The procedure begins by placing concrete into the upper hopper without any compaction. Once filled, the bottom door of this hopper is opened,...
Measurement: Derived Units03:02

Measurement: Derived Units

The International System of Units or SI system, by international agreement, has fixed measurement units for seven fundamental properties: length, mass, time, temperature, electric current, amount of substance, and luminosity. These are called the SI base units.
Measurement: Standard Units03:38

Measurement: Standard Units

Every measurement provides three kinds of information: the size or magnitude of the measurement (a number), a standard of comparison for the measurement (a unit), and an indication of the uncertainty of the measurement. While the number and unit are explicitly represented when a quantity is written, the uncertainty is an aspect of the errors in the measurement results.
Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
Measurements of Strain01:27

Measurements of Strain

Strain quantifies the deformation of a material under force, typically measured as normal strain, which represents the change in length when compared with the original length. Electrical strain gauges are used for enhanced accuracy. These devices consist of a conductive wire mounted on a paper backing that adheres to the material's surface. These gauges operate on the piezoresistive effect, where the wire's electrical resistance changes in response to mechanical deformation. The strain gauge...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

You might also read

Related Articles

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

Sort by
Same author

Forest Inspection Dataset: A Synthetic UAV Dataset for Semantic Segmentation of Forest Environments.

Scientific data·2026
Same author

Hepatocellular Carcinoma Recognition from Ultrasound Images Using Combinations of Conventional and Deep Learning Techniques.

Sensors (Basel, Switzerland)·2023
Same author

Enhanced Perception for Autonomous Driving Using Semantic and Geometric Data Fusion.

Sensors (Basel, Switzerland)·2022
Same author

Fast Panoptic Segmentation with Soft Attention Embeddings.

Sensors (Basel, Switzerland)·2022
Same author

Robust Data Association Using Fusion of Data-Driven and Engineered Features for Real-Time Pedestrian Tracking in Thermal Images.

Sensors (Basel, Switzerland)·2021
Same author

Hepatocellular Carcinoma Automatic Diagnosis within CEUS and B-Mode Ultrasound Images Using Advanced Machine Learning Methods.

Sensors (Basel, Switzerland)·2021
Same journal

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

GoP-based Quality Enhancement on Video Compression.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Align Then Tensorize: Multi-Level Consistent Anchor Graph Learning for Scalable Multi-View Clustering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Beyond Fidelity: Diverse Image Synthesis via Retrieval-Augmented Diffusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

Related Experiment Video

Updated: May 8, 2026

Measurement of Specific Mycobacterial Mistranslation Rates with Gain-of-function Reporter Systems
06:18

Measurement of Specific Mycobacterial Mistranslation Rates with Gain-of-function Reporter Systems

Published on: April 26, 2019

Label transfer by measuring compactness.

Robert Varga, Sergiu Nedevschi

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |August 20, 2013
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel automatic image annotation algorithm using a new similarity measure called compactness. This method efficiently compares low-level features and outperforms existing techniques.

    More Related Videos

    Quantifying Intermembrane Distances with Serial Image Dilations
    07:45

    Quantifying Intermembrane Distances with Serial Image Dilations

    Published on: September 28, 2018

    Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level
    08:29

    Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

    Published on: April 19, 2019

    Related Experiment Videos

    Last Updated: May 8, 2026

    Measurement of Specific Mycobacterial Mistranslation Rates with Gain-of-function Reporter Systems
    06:18

    Measurement of Specific Mycobacterial Mistranslation Rates with Gain-of-function Reporter Systems

    Published on: April 26, 2019

    Quantifying Intermembrane Distances with Serial Image Dilations
    07:45

    Quantifying Intermembrane Distances with Serial Image Dilations

    Published on: September 28, 2018

    Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level
    08:29

    Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

    Published on: April 19, 2019

    Area of Science:

    • Computer Vision
    • Machine Learning

    Background:

    • Automatic image annotation is crucial for organizing and retrieving visual data.
    • Existing methods often struggle with efficiency and accuracy in comparing image features.

    Purpose of the Study:

    • To introduce a new automatic image annotation algorithm.
    • To present a novel similarity measure called compactness for image comparison.
    • To develop an efficient label transfer technique for image annotation.

    Main Methods:

    • Introduced 'compactness' as a similarity measure based on low-level visual descriptors and feature cluster centers.
    • Developed a k-nearest neighbor (k-NN) based image annotation method utilizing compactness.
    • Devised a formalism for label transfer techniques and implemented several variations.

    Main Results:

    • Evaluated the algorithm on four diverse image annotation benchmarks.
    • Demonstrated that the compactness measure enables efficient low-level feature comparison.
    • The proposed method significantly outperforms many state-of-the-art annotation techniques.

    Conclusions:

    • The developed image annotation algorithm is accurate and efficient.
    • Compactness serves as an effective similarity measure for image feature comparison.
    • The label transfer approach offers a robust method for automatic image annotation.