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

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...

Types of Global Positioning System Surveys

Types of Global Positioning System Surveys

GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...

You might also read

Related Articles

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

Sort by

Same author

Bifunctional Precursor-Assisted Shell Growth and Exciton Dynamics of Highly Luminescent CuInS<sub>2</sub>/ZnS Quantum Dots.

Small (Weinheim an der Bergstrasse, Germany)·2026

Same author

Establishment of an N-Glycan Profiling Method for Three ERT Enzymes Used in Gaucher Disease Therapy.

Molecules (Basel, Switzerland)·2026

Same author

A meta-reasoning and dual-level cognitive decision-making approach for blind-spot safety in autonomous driving.

ISA transactions·2026

Same author

An integrated molecular characterization and simulation study of chain length effects on PFAS adsorption at hydrophobic interfaces.

Water research·2026

Same author

Fluorescence encoding technology based tetrahedral nano-string for logic identification of breast cancer cells.

Materials today. Bio·2026

Same author

Shell-thickness-modulated electrochemiluminescence of colloidal quantum dots for ultrasensitive PSA detection.

Biosensors & bioelectronics·2026

Search research articles

Related Experiment Video

Updated: Jun 21, 2025

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Research on high-speed classification and location algorithm for logistics parcels based on a monocular camera.

Zhehao Lu¹, Ning Dai², Xudong Hu¹

¹Key Laboratory of Modern Textile Machinery&Technology of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, 310018, China.

Scientific Reports

|July 10, 2024

Summary

This summary is machine-generated.

This study introduces a new algorithm using a monocular camera and YOLOv5 for high-speed logistics parcel sorting. It significantly improves positioning accuracy and efficiency in automated sorting systems.

Keywords:

High-speed logistics application Logistics parcel positioning Monocular camera algorithm YOLOv5

More Related Videos

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

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

Related Experiment Videos

Last Updated: Jun 21, 2025

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

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

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

Area of Science:

Computer Vision and Machine Learning
Logistics and Supply Chain Management
Robotics and Automation

Background:

Traditional light curtain methods struggle with the high-speed demands of modern logistics parcel sorting.
Limitations in precision and speed hinder the efficiency of automated logistics systems.
Need for advanced visual processing for real-time parcel identification and location.

Purpose of the Study:

To develop a high-speed, high-precision algorithm for logistics parcel classification and location.
To overcome the limitations of existing positioning technologies in fast-paced logistics environments.
To enhance the performance and efficiency of automated parcel sorting systems.

Main Methods:

Utilized a monocular camera for visual data acquisition.
Developed a novel algorithm combining traditional visual processing with an enhanced YOLOv5 object detection model.
Incorporated network structure adjustments, new feature extraction modules, and ECIOU loss functions for improved accuracy and robustness.

Main Results:

The proposed algorithm achieved high-speed and high-precision parcel positioning and classification.
Demonstrated significant improvements in model parameter efficiency and computational speed.
Exhibited outstanding performance on a customized logistics parcel dataset.

Conclusions:

The enhanced YOLOv5-based algorithm offers an effective solution for industrial applications in high-speed logistics.
The developed method addresses the critical need for accurate and rapid parcel handling in modern supply chains.
This approach provides a robust and efficient alternative to traditional positioning systems.