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

Structural Classification of Joints01:20

Structural Classification of Joints

Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
Structuralism01:26

Structuralism

Structuralism, an early psychological theory developed by Wilhelm Wundt and his student Edward Bradford Titchener, sought to dissect the human mind into its most fundamental components. Wundt's groundbreaking work in his laboratory set the stage for Titchener to define structuralism's goal as cataloging the "atoms" of the mind—sensations, images, and feelings—akin to how chemists identify elements of matter.
Titchener's approach to structuralism was unique. He employed introspection, a method...

You might also read

Related Articles

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

Sort by
Same author

Plant-sourced cooking oil consumption is associated with lower total mortality in a longitudinal nationwide cohort study.

Clinical nutrition (Edinburgh, Scotland)·2020
Same author

LINC01116 promotes tumor proliferation and neutrophil recruitment via DDX5-mediated regulation of IL-1β in glioma cell.

Cell death & disease·2020
Same author

Metal-Organic Framework Membrane Nanopores as Biomimetic Photoresponsive Ion Channels and Photodriven Ion Pumps.

Angewandte Chemie (International ed. in English)·2020
Same author

Graphdiyne oxide: a new carbon nanozyme.

Chemical communications (Cambridge, England)·2020
Same author

Egg and egg-sourced cholesterol consumption in relation to mortality: Findings from population-based nationwide cohort.

Clinical nutrition (Edinburgh, Scotland)·2020
Same author

A blood-based 22-gene expression signature for hepatocellular carcinoma identification.

Annals of translational medicine·2020
Same journal

Mask-guided Asymmetric Contrastive and Semantic Alignment for Unsupervised Person Re-Identification.

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

Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion.

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

Learning Gaze Synthesizer via 3D-eye Controlled Diffusion and Cross-domain Feature Alignment.

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

Underlying Semantic Diffusion for Effective and Efficient In-Context Learning.

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

DiffRES: Unleashing Text-to-Image Diffusion Models for Generative Referring Expression Segmentation without Information Leakage.

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

Location Matters: Frequency-Spatial Dual Space Adaptation for Cross-Domain Few-Shot Segmentation.

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

Related Experiment Video

Updated: May 25, 2026

Automated Joint Space Detection Improves Bone Segmentation Accuracy
06:45

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Published on: November 28, 2025

Image annotation by input-output structural grouping sparsity.

Yahong Han1, Fei Wu, Qi Tian

  • 1School of Computer Science and Technology, Tianjin University, Tianjin, China. hanyahong@gmail.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 21, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel bilayer regression model for automatic image annotation (AIA) that enhances image retrieval and understanding. The model effectively selects structured visual features and leverages hierarchical tag correlations for improved multitag image annotation performance.

More Related Videos

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Related Experiment Videos

Last Updated: May 25, 2026

Automated Joint Space Detection Improves Bone Segmentation Accuracy
06:45

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Published on: November 28, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Area of Science:

  • Computer Vision
  • Machine Learning
  • Artificial Intelligence

Background:

  • Automatic image annotation (AIA) is crucial for image retrieval and understanding.
  • Key challenges in AIA include selecting relevant visual features and modeling complex tag relationships.

Purpose of the Study:

  • To address limitations in AIA by proposing a novel regularized regression model.
  • To enhance multitag image annotation by incorporating structured feature selection and hierarchical label correlations.

Main Methods:

  • Introduced input and output structural grouping sparsity into a regularized regression model.
  • Developed a bilayer regression model (Bi-MtBGS) for efficient solving.
  • Implemented structured feature selection for group-wise and within-group feature selection.
  • Utilized tree-structured grouping sparsity to model hierarchical label correlations.

Main Results:

  • The proposed Bi-MtBGS model demonstrated superior performance in multitag image annotation on benchmark and real-world datasets.
  • The method achieved effective selection of heterogeneous features (color, texture, shape).
  • The model provided an interpretable framework for image understanding.

Conclusions:

  • The novel approach significantly improves multitag image annotation accuracy.
  • The structured feature selection and hierarchical label modeling are effective strategies for AIA.
  • The proposed method offers a robust and interpretable solution for image understanding tasks.