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

Application of Nonlinear Inequalities01:29

Application of Nonlinear Inequalities

150
A nonlinear inequality describes a comparison involving an expression that curves or behaves more complexly than a straight line. These inequalities often appear in forms that include squares, products, or variables in the denominator.To solve such an inequality, one starts by rewriting it so that zero appears on one side. For example, the inequality:  can be factored as: This form makes it easier to identify the values that cause the expression to equal zero. In this case, the...
150
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

794
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
794
Routh-Hurwitz Criterion I01:15

Routh-Hurwitz Criterion I

464
Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...
464
Functional Classification of Joints01:09

Functional Classification of Joints

6.3K
Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
6.3K
Aggregates Classification01:29

Aggregates Classification

884
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
884
Classification of Systems-II01:31

Classification of Systems-II

425
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
425

You might also read

Related Articles

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

Sort by
Same author

CLEAN: Category Knowledge-Driven Compression Framework for Efficient 3D Object Detection.

IEEE transactions on pattern analysis and machine intelligence·2025
Same author

Unified Framework for Faster Clustering via Joint Schatten p-Norm Factorization With Optimal Mean.

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

Toughening Ceramics down to Cryogenic Temperatures by Reentrant Strain-Glass Transition.

Physical review letters·2023
Same author

Proprotein Convertase Subtilisin/Kexin 9 (PCSK9) Promotes Macrophage Activation via LDL Receptor-Independent Mechanisms.

Circulation research·2022
Same author

Generalized Nonconvex Nonsmooth Low-Rank Matrix Recovery Framework With Feasible Algorithm Designs and Convergence Analysis.

IEEE transactions on neural networks and learning systems·2022
Same author

Systems Approach to Discovery of Therapeutic Targets for Vein Graft Disease: PPARα Pivotally Regulates Metabolism, Activation, and Heterogeneity of Macrophages and Lesion Development.

Circulation·2021
Same journal

A New Human-Likeness and Comfort Index for Robot Movements Along Prescribed Paths.

IEEE transactions on cybernetics·2026
Same journal

Robust Semiglobal and Global Stabilization for Nonlinear Normal Form Systems by Time-Varying Feedback.

IEEE transactions on cybernetics·2026
Same journal

Adaptive Global Asymptotic Output Stabilization of Uncertain Nonlinear Systems Under Dynamic State/Input Quantization.

IEEE transactions on cybernetics·2026
Same journal

Accelerated Distributed Gradient Tracking for Constrained Aggregative Optimization Over Time-Varying Digraphs.

IEEE transactions on cybernetics·2026
Same journal

Small-Gain-Based Plug-and-Play Distributed Control Framework for DC Microgrids With Decentralized Reconfiguration.

IEEE transactions on cybernetics·2026
Same journal

Prescribed-Time Impulsive Control of High-Order Integrator Systems.

IEEE transactions on cybernetics·2026
See all related articles

Related Experiment Video

Updated: Dec 20, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.5K

Joint Optimal Transport With Convex Regularization for Robust Image Classification.

Jianjun Qian, Wai Keung Wong, Hengmin Zhang

    IEEE Transactions on Cybernetics
    |May 27, 2020
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel robust regression model using optimal transport (OT) and convex regularization for high-dimensional visual data. The proposed method enhances image classification accuracy, particularly against structural noise and occlusions.

    More Related Videos

    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    9.8K
    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
    07:13

    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

    Published on: October 27, 2023

    1.6K

    Related Experiment Videos

    Last Updated: Dec 20, 2025

    Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
    08:27

    Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

    Published on: January 5, 2024

    1.5K
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    9.8K
    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
    07:13

    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

    Published on: October 27, 2023

    1.6K

    Area of Science:

    • Computer Vision
    • Machine Learning
    • Statistical Modeling

    Background:

    • Robust regression from high-dimensional visual data requires effective error term characterization.
    • Existing nuclear norm methods capture structural noise but ignore global distribution information.
    • Optimal Transport (OT) offers a robust metric for distribution comparison, handling element correspondences.

    Purpose of the Study:

    • To develop a novel robust regression scheme integrating Optimal Transport (OT) with convex regularization for visual data.
    • To improve image classification performance, especially under challenging conditions like illumination changes and occlusions.
    • To introduce and analyze new models, Optimal Transport-based Regression (OTR) and Extended OTR (EOTR).

    Main Methods:

    • Proposed OT-based regression with L2 norm regularization (OTR) for image classification.
    • Developed an Extended OTR (EOTR) model by incorporating a nuclear norm error term to address occlusions.
    • Utilized the alternating direction method of multipliers (ADMM) for model optimization, including Gaussian back substitution for EOTR.
    • Provided complexity and convergence analysis for the developed algorithms.

    Main Results:

    • The OTR and EOTR models demonstrated robust performance on biometric image classification tasks.
    • Experimental results on five benchmark datasets confirmed superior performance against state-of-the-art methods.
    • The models effectively handled structural noises, including illumination variations and various forms of occlusion.

    Conclusions:

    • The novel OT-integrated robust regression framework offers significant improvements in visual data analysis and classification.
    • The EOTR model specifically addresses occlusion challenges, enhancing classification reliability.
    • The proposed methods represent a significant advancement in robust regression for high-dimensional visual data classification.