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

Association Areas of the Cortex01:21

Association Areas of the Cortex

7.0K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
7.0K
Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

324
Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role...
324
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

629
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
629

You might also read

Related Articles

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

Sort by
Same author

Nonlinear hydrothermal associations between coupled landscape ecological risk and resilience in a major grain-producing region of China.

Journal of environmental management·2026
Same author

LangSurf: Language-Embedded Surface Gaussians for 3D Scene Understanding.

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

Breathing New Life into Small Object Detection with Detection-Oriented Rectification.

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

A novel multi-task deep learning framework for classification and detection of intracranial structures in first-trimester fetal ultrasound images.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026
Same author

PathTIGR: A pathway topology-informed graph representation learning framework for immunotherapy response prediction.

Science advances·2026
Same author

Interpretable graph deep learning framework for drug synergy prediction by integrating functional and clinical similarities.

NPJ digital medicine·2026
Same journal

Hidden Data Recovery and Forecasting via Next-Generation Reservoir Computing With Multiscale Delay Selection.

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

CAFF-CIL: Causality-Aware Freedom Forgetting Approach for Class-Incremental Learning.

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

Harmonic Autoencoding Framework for Multiple Tasks in Magnetic Particle Imaging Reconstruction.

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

A Survey on Human-Centric Voice-Face Multimodal Learning.

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

Vision-Assisted Foundation Model for Solving Multitask Vehicle Routing Problems.

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

FP3O: Enabling Proximal Policy Optimization in Multiagent Cooperation With Parameter-Sharing Versatility.

IEEE transactions on neural networks and learning systems·2026
See all related articles

Related Experiment Video

Updated: Oct 22, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

708

CLRNet: Component-Level Refinement Network for Deep Face Parsing.

Peiliang Huang, Junwei Han, Dingwen Zhang

    IEEE Transactions on Neural Networks and Learning Systems
    |August 30, 2021
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new face parsing method, CLRNet, which precisely segments facial components. It improves accuracy, especially for small features, by integrating context and attention mechanisms for better joint optimization.

    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

    9.5K
    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    576

    Related Experiment Videos

    Last Updated: Oct 22, 2025

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    708
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    9.5K
    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    576

    Area of Science:

    • Computer Vision
    • Artificial Intelligence

    Background:

    • Face parsing assigns pixel-level labels to facial components, but struggles with accuracy, particularly for small features.
    • Existing methods often use independent cropping and segmentation stages, hindering joint optimization.
    • Contextual information for facial component parsing remains underexplored.

    Purpose of the Study:

    • To develop a precise face parsing method that overcomes limitations of existing approaches.
    • To improve segmentation accuracy, especially for tiny facial components.
    • To effectively utilize contextual information in the face parsing process.

    Main Methods:

    • Proposed a Component-Level Refinement Network (CLRNet) for precise face parsing.
    • Introduced an attention mechanism to create an end-to-end trainable pipeline, bridging independent stages.
    • Incorporated global context information into the refinement of cropped facial component patches.

    Main Results:

    • CLRNet demonstrated superior performance over state-of-the-art methods on LFW-PL and HELEN datasets.
    • The method showed significant improvements in segmenting tiny facial components.
    • The attention mechanism and context incorporation proved effective for accurate parsing.

    Conclusions:

    • CLRNet offers a more accurate and robust solution for face parsing, particularly for challenging small facial features.
    • The end-to-end trainable pipeline with attention and context integration represents a significant advancement in the field.
    • The proposed approach effectively leverages global context for improved facial component segmentation.