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

Super-resolution Fluorescence Microscopy

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...

You might also read

Related Articles

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

Sort by

Same author

The Airway Epithelial Barrier in Childhood Asthma: A Central Player in Glucocorticoid Therapy, Resistance, and Severe Asthma.

Pediatric discovery·2026

Same author

Macrophage-Specific SPP1 Contributes to Pressure Overload-Induced Cardiac Dysfunction and Maladaptive Remodeling.

JACC. Basic to translational science·2026

Same author

A novel metal-free sling approach for benign prostatic hyperplasia: early results of the Progator procedure with high ejaculatory preservation.

Translational andrology and urology·2026

Same author

Glucocorticoids injure the airway epithelial barrier via endoplasmic reticulum stress-related apoptosis in asthma.

Frontiers in pharmacology·2026

Same author

Discovery of twelve undescribed diterpenoid alkaloids and identification of shawurensine A as a potent α7 nAChR antagonist.

Phytochemistry·2026

Same author

<i>LINC02470</i> impairs natural killer cell cytotoxicity by epigenetically targeting the natural cytotoxicity triggering receptor 1.

Frontiers in immunology·2026

Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026

Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026

Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026

Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026

Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026

Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 28, 2025

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

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

Published on: December 15, 2023

Attention Network with Information Distillation for Super-Resolution.

Huaijuan Zang¹, Ying Zhao¹, Chao Niu¹

¹Key Laboratory of Knowledge Engineering with Big Data, Ministry of Education, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China.

Entropy (Basel, Switzerland)

|September 23, 2022

Summary

This summary is machine-generated.

This study introduces an efficient attention network with information distillation (AIDN) for accurate image super-resolution. AIDN improves visual quality and reconstruction accuracy while reducing computational costs.

Keywords:

attention mechanism distillation structure image super-resolution

More Related Videos

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

Related Experiment Videos

Last Updated: Aug 28, 2025

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

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

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

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

Area of Science:

Computer Vision
Artificial Intelligence
Image Processing

Background:

Image super-resolution (SR) models using deep convolutional neural networks (CNNs) have advanced visual quality.
Existing SR models face challenges with high computational costs and underutilization of intermediate features.

Purpose of the Study:

To develop an efficient and accurate image super-resolution model.
To address the limitations of high computational costs and feature underutilization in current SR models.

Main Methods:

Proposed an attention network with information distillation (AIDN).
Introduced gated channel transformation (GCT) for global channel context.
Developed a recalibrated attention module (RAM) for spatial feature rescaling.

Main Results:

AIDN adaptively modulates feature responses by modeling channel and spatial interactions.
GCT and RAM jointly enhance information identification capabilities.
Achieved improved computational efficiency and reconstruction accuracy.

Conclusions:

AIDN outperforms state-of-the-art models in reconstruction performance and visual quality.
The proposed model offers a practical solution for efficient and accurate image super-resolution.