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 Experiment Video

Updated: Jul 11, 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

564

Hybrid-Input Convolutional Neural Network-Based Underwater Image Quality Assessment.

Wei Liu, Rongxin Cui, Yinglin Li

    IEEE Transactions on Neural Networks and Learning Systems
    |November 9, 2023
    PubMed
    Summary

    This study introduces a hybrid-input convolutional neural network (HI-CNN) to predict underwater image degradation. This method aids in selective image transmission, improving the efficiency of remotely operated vehicles (ROVs).

    Related Concept Videos

    You might also read

    Related Articles

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

    Sort by
    Same author

    Efficacy and safety of plant-derived bioactive compounds in the treatment of psoriasis vulgaris: a systematic review and network meta-analysis.

    Frontiers in medicine·2026
    Same author

    Signal-amplified cell-free biosensing of antibiotics using tandem fluorescent aptamers.

    Talanta·2026
    Same author

    An Easy-To-Use and Field-Deployable Cell-Free Bioreporter for Environmental Detection of Tetracyclines and Macrolides.

    Analytical chemistry·2026
    Same author

    Mechanistic Insights into Qin Bi Yin for Psoriasis Treatment Using Network Pharmacology, Experimental Validation, and Molecular Docking.

    Journal of inflammation research·2025
    Same author

    Comprehensive assessment of antibiotic impacts and risk thresholds on aquatic microbiomes and resistomes.

    Water research·2025
    Same author

    Transmission and control strategies of antimicrobial resistance from the environment to the clinic: A holistic review.

    The Science of the total environment·2024

    Area of Science:

    • Computer Vision
    • Robotics
    • Image Processing

    Background:

    • Underwater operations require precise environmental sensing, driving interest in underwater image processing.
    • Remotely operated vehicles (ROVs) generate redundant underwater images, pressuring equipment and operators.
    • Selective image transmission based on degradation is needed to alleviate this pressure.

    Purpose of the Study:

    • To propose an end-to-end hybrid-input convolutional neural network (HI-CNN) for predicting underwater image degradation.
    • To develop a model that enables selective image transmission, reducing data load.
    • To establish a real-world dataset for practical underwater environments.

    Main Methods:

    • A feature extraction module concurrently processes original underwater images and saliency maps using two identical, shared-parameter branches.

    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

    9.2K
    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
    04:23

    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

    Published on: April 21, 2023

    1.9K

    Related Experiment Videos

    Last Updated: Jul 11, 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

    564
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    9.2K
    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
    04:23

    A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

    Published on: April 21, 2023

    1.9K
  • An end-to-end model integrates the feature extraction module with a prediction module to estimate image quality scores.
  • A real-world dataset was created to validate the model in practical underwater scenarios.

    • Main Results:

    • The proposed HI-CNN model effectively predicts the degradation of underwater images.
    • Experimental results demonstrate the model's superior performance compared to existing methods.
    • The model facilitates selective image transmission based on predicted quality.

    Conclusions:

    • The developed HI-CNN offers a robust solution for assessing underwater image quality.
    • This approach can significantly enhance the efficiency and reliability of underwater operations.
    • The established dataset supports further research and practical application of underwater image processing techniques.