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

Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

413
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
413
Protein Networks02:26

Protein Networks

4.5K
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,...
4.5K
Protein Networks02:26

Protein Networks

2.9K
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
Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

498
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
498
Attention-Deficit/Hyperactivity Disorder01:30

Attention-Deficit/Hyperactivity Disorder

980
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by persistent inattention, hyperactivity, and impulsivity. It affects approximately 5-8% of children globally, with around 60-70% of cases persisting into adulthood. ADHD has significant implications for educational attainment, social interactions, and occupational success.
Diagnostic Criteria and Symptoms
To diagnose ADHD, symptoms must manifest before age 12 and be evident across multiple settings....
980

You might also read

Related Articles

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

Sort by
Same author

Multi-Stage Network With Geometric Semantic Attention for Two-View Correspondence Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2024
Same author

Fractional Amplitude of Low-Frequency Fluctuation and Voxel-Mirrored Homotopic Connectivity in Patients with Persistent Postural-Perceptual Dizziness: Resting-State Functional Magnetic Resonance Imaging Study.

Brain connectivity·2024
Same author

Sinkhorn Distance Minimization for Adaptive Semi-Supervised Social Network Alignment.

IEEE transactions on neural networks and learning systems·2023
Same author

Cross-Attentional Spatio-Temporal Semantic Graph Networks for Video Question Answering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2022
Same author

Multilevel Attention Networks and Policy Reinforcement Learning for Image Caption Generation.

Big data·2021
Same author

Visual Sentiment Analysis With Social Relations-Guided Multiattention Networks.

IEEE transactions on cybernetics·2020

Related Experiment Video

Updated: Feb 2, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.6K

Bi-directional Spatial-Semantic Attention Networks for Image-Text Matching.

Feiran Huang, Xiaoming Zhang, Zhoujun Li

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |November 20, 2018
    PubMed
    Summary

    This study introduces Bi-directional Spatial-Semantic Attention Networks (BSSAN) for improved image-text matching. BSSAN effectively models complex word-region and object-word relationships, achieving state-of-the-art results.

    More Related Videos

    A Semantic Priming Event-related Potential ERP Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder
    08:17

    A Semantic Priming Event-related Potential ERP Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder

    Published on: April 12, 2018

    11.1K
    Spatial Molecular Imaging of the Glycome Using Mass Spectrometry
    08:52

    Spatial Molecular Imaging of the Glycome Using Mass Spectrometry

    Published on: November 28, 2025

    535

    Related Experiment Videos

    Last Updated: Feb 2, 2026

    Modeling the Functional Network for Spatial Navigation in the Human Brain
    05:55

    Modeling the Functional Network for Spatial Navigation in the Human Brain

    Published on: October 13, 2023

    1.6K
    A Semantic Priming Event-related Potential ERP Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder
    08:17

    A Semantic Priming Event-related Potential ERP Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder

    Published on: April 12, 2018

    11.1K
    Spatial Molecular Imaging of the Glycome Using Mass Spectrometry
    08:52

    Spatial Molecular Imaging of the Glycome Using Mass Spectrometry

    Published on: November 28, 2025

    535

    Area of Science:

    • Computer Vision
    • Artificial Intelligence
    • Natural Language Processing

    Background:

    • Deep models excel at image-text matching tasks like captioning and search.
    • Modeling complex relationships between images and text is challenging for current methods.

    Purpose of the Study:

    • To develop a novel deep framework for enhanced image-text matching.
    • To effectively model both word-to-region and object-to-word relations.

    Main Methods:

    • Introduced Bi-directional Spatial-Semantic Attention Networks (BSSAN).
    • Employed LSTM with bilinear attention for word-to-region (W2R) attention.
    • Developed an object-to-word (O2W) attention network to link visual objects with semantic words.

    Main Results:

    • BSSAN unifies W2R and O2W attention in a holistic framework.
    • The proposed approach achieves state-of-the-art performance.
    • Evaluated on Flickr30K and MSCOCO datasets.

    Conclusions:

    • BSSAN offers a more effective approach to image-text matching.
    • Holistic modeling of bi-directional spatial-semantic relations is crucial for performance.