Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Association Areas of the Cortex

Association Areas of the Cortex

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,...

Neural Circuits

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...

Parallel Processing

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

You might also read

Related Articles

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

Sort by

Same author

HER2 assessment in locally advanced gastric cancer: comparing the results obtained with the use of two primary tumour blocks versus those obtained with the use of all primary tumour blocks.

Histopathology·2017

Same author

Inflammatory microRNA-194 and -515 attenuate the biosynthesis of chondroitin sulfate during human intervertebral disc degeneration.

Oncotarget·2017

Same author

Soil Acidification Aggravates the Occurrence of Bacterial Wilt in South China.

Frontiers in microbiology·2017

Same author

Is the Prophylactic Use of Hepatoprotectants Necessary in Anti-Tuberculosis Treatment?

Chemotherapy·2017

Same author

Light-induced aggregation of microbial exopolymeric substances.

Chemosphere·2017

Same author

Chemical Synthesis of (+)-Ryanodine and (+)-20-Deoxyspiganthine.

ACS central science·2017

Same journal

Anchor-based disentanglement framework for incremental multi-view clustering.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Complex-valued amplitude-phase interference modeling for adversarially robust classification.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

TraNce: Type-aware hypergraph neural network with biological mediators for drug repositioning.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Decentralized ADMM for factorization-based Low-rank matrix estimation.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Memristive neuromorphic circuit design inspired by the neural mechanisms of conditioned fear.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Q-learning based asynchronous Boolean control networks stabilization with data loss.

Neural networks : the official journal of the International Neural Network Society·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 28, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

EMBANet: A flexible efficient multi-branch attention network.

Keke Zu¹, Hu Zhang², Lei Zhang³

¹Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, Zhejiang, China; Shenzhen Key Laboratory of Advanced Machine Learning and Applications, Shenzhen University, Shenzhen, China.

Neural Networks : the Official Journal of the International Neural Network Society

|February 14, 2025

Summary

This summary is machine-generated.

This study introduces the Multi-Branch Attention (MBA) module for convolutional neural networks, enhancing multi-scale feature representation and long-range channel dependencies for improved computer vision performance.

Keywords:

Degrees of freedom EMBANet Flexible operation structure Multi-branch attention

More Related Videos

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

Related Experiment Videos

Last Updated: May 28, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

Area of Science:

Computer Vision
Deep Learning
Artificial Intelligence

Background:

Convolutional Neural Networks (CNNs) performance relies on multi-scale feature representation.
Existing methods often increase computational cost or neglect structural information and long-range channel dependencies.

Purpose of the Study:

Introduce a novel Multi-Branch Concatenation (MBC) module for enhanced multi-scale feature extraction.
Develop a Multi-Branch Attention (MBA) module to capture channel-wise interactions and long-range dependencies.
Propose an Efficient Multi-Branch Attention (EMBA) block and EMBANet backbone for CNNs.

Main Methods:

Designed the Multi-Branch Concatenation (MBC) module with flexible transformation operators (multiplexing, splitting).
Integrated MBC with attention mechanisms to create the Multi-Branch Attention (MBA) module.
Replaced ResNet bottleneck convolutions with EMBA blocks to form the EMBANet backbone.

Main Results:

The MBC module allows flexible adjustments in attention networks, improving multi-scale feature representation.
The MBA module effectively captures channel-wise interactions, establishing long-range channel dependencies.
EMBANet demonstrated superior performance across classification, detection, and segmentation tasks compared to existing backbones.

Conclusions:

The proposed MBA module and EMBANet backbone offer an efficient approach to enhance CNN performance.
EMBANet provides a robust solution for various computer vision applications by improving feature representation and dependencies.
This work advances CNN design by effectively integrating multi-scale feature extraction and attention mechanisms.