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

Chunking and Rehearsal in Sensory Memory01:22

Chunking and Rehearsal in Sensory Memory

731
Improving short-term memory can be achieved through techniques like chunking and rehearsal. Chunking involves organizing information into larger, more manageable units. This technique is particularly useful for information that exceeds the typical memory span of between five and nine items. For instance, logging into an online account with a password like "ta89vq0179gz" involves grouping letters and numbers into three chunks—ta89, vq01, and 79gz. It makes large amounts of...
731
The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

7.9K
In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
7.9K

You might also read

Related Articles

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

Sort by
Same author

Association between oxidative balance score, genetic susceptibility and nephrolithiasis: a cohort study based on the UK Biobank.

European journal of nutrition·2026
Same author

The combined toxic effects of long-term exposure to environmentally relevant concentrations of imidacloprid and chromium on Xenopus laevis tadpoles: Growth, oxidative stress, and molecular mechanisms.

Ecotoxicology and environmental safety·2026
Same author

Design, synthesis, antibacterial activity evaluation, and mechanism of action study of novel pyrrolidine derivatives containing sulfonamide structures.

Molecular diversity·2026
Same author

Design, synthesis, antibacterial activity, and mechanism study of phosphate-containing vanillin sulfonylhydrazide derivatives.

Pest management science·2026
Same author

Machine Learning-Based Accurate Full-Sib Family Assignment in Sturgeon Using Whole-Genome Sequencing Data.

International journal of molecular sciences·2026
Same author

Investigation of Antibacterial Activity and Mechanism of Action: Design and Synthesis of Phosphonate Derivatives Containing Sulfonate Ester Groups.

Journal of agricultural and food chemistry·2026
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: Mar 27, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.4K

Sparse Contextual Activation for Efficient Visual Re-Ranking.

Song Bai, Xiang Bai

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |January 8, 2016
    PubMed
    Summary
    This summary is machine-generated.

    We introduce a fast visual re-ranking algorithm using sparse contextual activation (SCA) feature vectors. This method achieves efficient image retrieval with an average re-ranking time of 1 ms, enhancing search performance.

    More Related Videos

    Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
    05:58

    Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

    Published on: August 29, 2018

    9.4K
    Cross-Modal Multivariate Pattern Analysis
    13:51

    Cross-Modal Multivariate Pattern Analysis

    Published on: November 9, 2011

    20.6K

    Related Experiment Videos

    Last Updated: Mar 27, 2026

    Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
    13:00

    Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

    Published on: January 23, 2017

    10.4K
    Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
    05:58

    Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

    Published on: August 29, 2018

    9.4K
    Cross-Modal Multivariate Pattern Analysis
    13:51

    Cross-Modal Multivariate Pattern Analysis

    Published on: November 9, 2011

    20.6K

    Area of Science:

    • Computer Vision
    • Machine Learning
    • Information Retrieval

    Background:

    • Visual re-ranking is crucial for improving search results in large-scale image databases.
    • Existing methods often face challenges with computational efficiency and retrieval accuracy.
    • The need for fast and accurate visual re-ranking algorithms is paramount.

    Purpose of the Study:

    • To propose an extremely efficient algorithm for visual re-ranking.
    • To develop a novel feature vector, sparse contextual activation (SCA), for encoding image local distribution.
    • To enhance retrieval performance and time efficiency in visual search tasks.

    Main Methods:

    • Developed sparse contextual activation (SCA) feature vectors by considering pairwise distance in contextual space.
    • Employed generalized Jaccard metric for vector comparison in re-ranking.
    • Introduced inverted index to accelerate generalized Jaccard metric computation, achieving an average re-ranking time of 1 ms.
    • Implemented local consistency enhancement for unsupervised performance improvement.
    • Utilized a robust feature fusion algorithm based on SCA for enhanced accuracy.

    Main Results:

    • The proposed SCA method significantly improves the efficiency of visual re-ranking, with average query re-ranking time under 1 ms.
    • Local consistency enhancement boosts retrieval performance in an unsupervised manner.
    • Feature fusion based on SCA further enhances retrieval accuracy while maintaining high time efficiency.
    • Experiments on diverse datasets (Princeton shape, WM-SRHEC07, YAEL, MPEG-7, Ukbench) demonstrate the method's effectiveness.

    Conclusions:

    • The proposed sparse contextual activation (SCA) algorithm offers a highly efficient and effective solution for visual re-ranking.
    • The integration of inverted index and feature fusion contributes to both speed and accuracy.
    • SCA shows broad applicability across various visual re-ranking tasks and datasets.