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

Guidelines for Sketching a Curve01:23

Guidelines for Sketching a Curve

120
Curve sketching is a systematic method for understanding the overall behavior of a function by analyzing its key mathematical features. A function defines a curve on the coordinate plane, where the horizontal axis represents the input variable and the vertical axis represents the output. The process begins by determining the domain, which specifies the set of input values for which the function is defined and establishes the horizontal extent of the graph.Intercepts with the horizontal and...
120
Curve Sketching and Derivatives01:22

Curve Sketching and Derivatives

63
Understanding the behavior of a function through its first and second derivatives is essential for analyzing its graph. Derivatives provide insight into where a function increases or decreases, where it attains local maxima or minima, and how its curvature behaves across different intervals.The first derivative of a function reveals the slope of the tangent line at any given point. Points where the derivative is zero or undefined are considered critical, as they often indicate potential extrema...
63
Attachment Styles01:24

Attachment Styles

402
Jeffrey Simpson's attachment theory suggests that early caregiver relationships shape lasting patterns of behavior and emotional regulation, known as attachment styles. These patterns are organized along two key dimensions: self-esteem and interpersonal trust. The intersection of these dimensions produces four primary attachment styles that typically persist throughout life and significantly influence how individuals form and maintain relationships.Secure Attachment StyleIndividuals with a...
402
Parenting Styles01:27

Parenting Styles

648
Diana Baumrind's four parenting styles — authoritarian, authoritative, neglectful, and permissive — each influence children's socio-emotional development differently.
Authoritarian Parenting
This style is strict and controlling, with little room for open dialogue. Authoritarian parents demand obedience and often enforce rules with minimal warmth. Children raised this way may lack social skills and initiative, usually comparing themselves to others unfavorably.
Authoritative...
648
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

245
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
245
Hazan and Shaver's Attachment Styles01:28

Hazan and Shaver's Attachment Styles

458
Attachment theory, developed initially to explain infant–caregiver bonds, has been extended to illuminate patterns of intimacy in adult romantic relationships. Psychologists Cindy Hazan and Phillip Shaver proposed that the attachment styles observed in infancy form a framework for how individuals approach emotional closeness and conflict in adulthood. These attachment styles—secure, avoidant, and anxious—are linked to enduring patterns of behavior and emotional regulation in...
458

You might also read

Related Articles

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

Sort by
Same author

Benefiting From OOD Samples in Open-Set Semi-Supervised Object Detection.

IEEE transactions on neural networks and learning systems·2026
Same author

Targeting the Light-Harvesting Complex I Gene Lhca4 Confers Saline-Alkali Tolerance in Rice Without Yield Penalty.

Plant, cell & environment·2026
Same author

DreamFuse: Towards Realistic and Seamless Image Fusion Across Diverse Scenarios.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Disruption of spike protein N-glycosylation induces its endoplasmic reticulum retention and attenuates SARS-CoV-2 infectivity.

Journal of virology·2026
Same author

Impedance-driven capacitance amplification in dielectric gradient all-fiber non-ionic electronic skin.

Nature communications·2026
Same author

Biomimetic All-Wood Sponge for the Co-Generation of Adsorption-Based Atmospheric Water Harvesting and Hydrovoltaic Power Generation.

Research (Washington, D.C.)·2026
Same journal

Graph Pattern Matching based reassembly - 3DGPM.

IEEE computer graphics and applications·2026
Same journal

Making Learning Visible: Turning Public Engagement into Evidence for Academic Learning.

IEEE computer graphics and applications·2026
Same journal

LlymX: Multimodal LLM-Augmented XR for Context-Aware Information Access.

IEEE computer graphics and applications·2026
Same journal

Dynamic Gaussian-Based Digital Twin Reconstruction of Articulated Multi-Joint Objects.

IEEE computer graphics and applications·2026
Same journal

Steiner and Poisson Traversal Initializations: Initial Curve Optimization for Geometric Flow-based Surface Filling.

IEEE computer graphics and applications·2026
Same journal

Insight Into the Insight Toolkit.

IEEE computer graphics and applications·2026
See all related articles

Related Experiment Video

Updated: Jan 29, 2026

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.5K

Automatic Color Sketch Generation Using Deep Style Transfer.

Wei Zhang, Guanbin Li, Haoyu Ma

    IEEE Computer Graphics and Applications
    |February 15, 2019
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an automatic system for generating vivid color sketches by adapting real-time style transfer methods. The novel approach enhances high-resolution image stylization, significantly reducing artifacts for realistic sketch outputs.

    More Related Videos

    Generation of Greater Bacterial Biofilm Biomass using PCR-Plate Deep Well Microplate Devices
    10:57

    Generation of Greater Bacterial Biofilm Biomass using PCR-Plate Deep Well Microplate Devices

    Published on: April 22, 2022

    9.0K
    Application of 3D Printing in the Construction of Burr Hole Ring for Deep Brain Stimulation Implants
    09:02

    Application of 3D Printing in the Construction of Burr Hole Ring for Deep Brain Stimulation Implants

    Published on: September 7, 2019

    7.4K

    Related Experiment Videos

    Last Updated: Jan 29, 2026

    Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
    08:20

    Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

    Published on: October 27, 2023

    2.5K
    Generation of Greater Bacterial Biofilm Biomass using PCR-Plate Deep Well Microplate Devices
    10:57

    Generation of Greater Bacterial Biofilm Biomass using PCR-Plate Deep Well Microplate Devices

    Published on: April 22, 2022

    9.0K
    Application of 3D Printing in the Construction of Burr Hole Ring for Deep Brain Stimulation Implants
    09:02

    Application of 3D Printing in the Construction of Burr Hole Ring for Deep Brain Stimulation Implants

    Published on: September 7, 2019

    7.4K

    Area of Science:

    • Computer Vision
    • Deep Learning
    • Image Processing

    Background:

    • Deep learning enables image style transfer, but challenges remain for color sketches due to unique textures.
    • Existing methods struggle with high-resolution and artifact reduction in sketch style transfer.

    Purpose of the Study:

    • To develop an automatic system for generating high-resolution color sketches from real-time style transfer.
    • To improve the quality and reduce artifacts in generated color sketch images.

    Main Methods:

    • Utilized real-time style transfer techniques with carefully selected color sketch examples as style targets.
    • Proposed a novel convolutional neural network with spatial refinement for high-resolution style transfer.
    • Incorporated gouache color effects using linear color transform and guided filtering.

    Main Results:

    • The system successfully generates vivid color sketch images.
    • Achieved significant reduction in artifacts compared to state-of-the-art methods.
    • Demonstrated effective high-resolution style transfer for color sketches.

    Conclusions:

    • The developed system offers an effective solution for automatic color sketch generation.
    • The novel network architecture and color transformation techniques improve sketch quality and realism.
    • This work advances the field of style transfer for artistic image generation.