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

Modeling and Similitude

Modeling and Similitude

Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...

You might also read

Related Articles

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

Sort by

Same author

Study on vapor-liquid equilibrium and process design for separation of ethyl propionate-<i>n</i>-propanol azeotropes with acetate ionic liquid.

RSC advances·2026

Same author

Aerial small object detection via dynamic convolution and hierarchical attention fusion for UAV imagery.

Scientific reports·2026

Same author

Cell-Resolved Mass Spectrometry Imaging Integrated with Isotope Tracing Elucidates Macrophage Polarization-Specific Metabolic Reprogramming.

Analytical chemistry·2026

Same author

A ZIF90-tungsten-based nanoparticle hydrogel system with antibacterial and antioxidant properties promotes periodontal bone regeneration by modulating the ROS/Plagl1/Wnt pathway.

Biomaterials·2026

Same author

CEDR: robust consensus cancer subtyping with multi-omics data via ensemble dimensionality reduction.

Briefings in bioinformatics·2026

Same author

Self-propelled nanozyme motors for targeted therapy of radiation cystitis by disrupting the inflammation-cfDNA vicious cycle.

Journal of nanobiotechnology·2026

Search research articles

Related Experiment Video

Updated: May 5, 2026

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Published on: March 6, 2014

Small fishing boat classification and recognition method based on GASF temporal graph coding and EMPViT model.

Jiaqi Deng¹, Xin Liu², Gang Du²

¹Southwest Institute of Electronic Technology, Chengdu, 610036, China. djqjecky@163.com.

Scientific Reports

|February 7, 2025

Summary

This summary is machine-generated.

This study introduces a novel method for identifying small fishing vessels using Gramian Summation Angular Field (GASF) image encoding and an enhanced Efficiency MPViT (EMPViT) model. The approach achieves high accuracy in complex environments, improving ship management.

Keywords:

Classification and recognition of small fishing boats EMPViT deep learning model GASF time series images One-dimensional time series coding Polynomial fitting

More Related Videos

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Published on: November 20, 2017

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

Related Experiment Videos

Last Updated: May 5, 2026

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Published on: March 6, 2014

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Published on: November 20, 2017

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

Area of Science:

Marine Engineering
Computer Vision
Artificial Intelligence

Background:

Effective management of small fishing vessels is crucial.
Current identification methods face challenges in complex environments.
Accurate classification of small fishing vessels is needed for enhanced maritime surveillance and resource management.

Purpose of the Study:

To propose a robust classification and recognition method for small fishing vessels.
To address the complexities of the recognition environment for small fishing boats.
To improve the accuracy and performance of small fishing vessel identification systems.

Main Methods:

Utilized a high-precision laser sensor for one-dimensional contour data acquisition.
Employed polynomial fitting for contour shape delineation.
Encoded contour data into two-dimensional time series images using Gramian Summation Angular Field (GASF).
Applied an enhanced Efficiency MPViT (EMPViT) model for classification and identification.

Main Results:

The GASF encoding and EMPViT model achieved a peak accuracy of 99.98% for small fishing vessel classification.
Ablation experiments confirmed the superiority of the EMPViT model over traditional CNN and ViT models.
Demonstrated high accuracy and performance in challenging recognition scenarios.

Conclusions:

The proposed GASF sequence diagram coding and EMPViT model offer a highly effective solution for small fishing vessel identification.
This method significantly enhances the accuracy and performance compared to existing approaches.
The findings contribute to improved ship management and maritime surveillance capabilities.