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 Concept Videos

Personal Protective Equipment01:20

Personal Protective Equipment

2.5K
Personal protective equipment (PPE) is unique clothing or equipment worn by an employee to minimize or prevent exposure to infectious agents. PPE creates a barrier between the employee and the infectious materials. PPE must be readily available in the patient care area. PPE includes gloves, gowns and aprons, masks and respirators, goggles, face shields, shoes, and headcovers:
2.5K
Force Classification01:22

Force Classification

2.7K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
2.7K
Detection of Black Holes01:10

Detection of Black Holes

2.6K
Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
Not until the 1960s, when the first neutron...
2.6K

You might also read

Related Articles

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

Sort by
Same author

Electronic structure engineering of molybdenum carbides for efficient water electrolysis.

Chemical communications (Cambridge, England)·2026
Same author

Visual neurotoxicity of zinc oxide nanoparticles on zebrafish larvae: Roles of retinal injury, redox imbalance, and impaired phototransduction.

Comparative biochemistry and physiology. Toxicology & pharmacology : CBP·2026
Same author

Machine learning-assisted Au@UiO-66-NH<sub>2</sub>-based electrochemical sensor for detection of ubiquitous heavy metal ions.

Talanta·2026
Same author

Lycopene-mediated mitigation of cadmium-induced nephrotoxicity in broilers is associated with restoring mitochondrial homeostasis.

Poultry science·2026
Same author

Dopamine neurons in the ventral tegmental area regulate emotional disturbances in a mouse model of acute respiratory distress syndrome.

Science bulletin·2026
Same author

Determination of micro/nanoplastics on the surface of polystyrene lunch boxes by pyrolysis-gas chromatography/mass spectrometry combined with efficient magnetic capture by Fe<sub>3</sub>O<sub>4</sub> nanoparticles.

Food chemistry·2026

Related Experiment Video

Updated: Apr 15, 2026

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

11.3K

Lightweight Safety Helmet Wearing Detection Algorithm Based on GSA-YOLO.

Haodong Wang1,2, Qiang Zhou1,2, Zhiyuan Hao1,2

  • 1Shandong Provincial Key Laboratory of New Power Distribution & Utilization Technology and Equipment, Shandong University of Technology, Zibo 255000, China.

Sensors (Basel, Switzerland)
|April 14, 2026
PubMed
Summary
This summary is machine-generated.

A new lightweight algorithm, GSA-YOLO, accurately detects safety helmets in challenging power station confined spaces. This system improves worker safety by overcoming lighting variations and small object detection issues with fewer parameters for field deployment.

Keywords:
GhostConvI-ECA mechanismWIoUYOLOsafety helmet testing

Related Experiment Videos

Last Updated: Apr 15, 2026

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

11.3K

Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Industrial Safety

Background:

  • Confined spaces in electric power stations present high risks due to severe illumination variations.
  • Proper safety helmet usage is critical for worker safety, but detection is challenging.
  • Existing object detection models are often too large for real-time deployment on resource-limited field devices.

Purpose of the Study:

  • To develop a lightweight and efficient safety helmet detection algorithm for confined spaces.
  • To address challenges of drastic illumination changes and small object detection.
  • To enable real-time helmet detection on field devices with limited computational resources.

Main Methods:

  • Proposed GSA-YOLO algorithm incorporating GCA-C2f module (GhostConv and CBAM) for enhanced feature extraction under varied lighting.
  • Integrated improved efficient channel attention (I-ECA) in the neck for better occluded target detection.
  • Added P2 detection branch and WIoU loss function to the head for improved small object detection and localization.
  • Utilized a custom 5000-image confined space helmet detection dataset for training and validation.

Main Results:

  • GSA-YOLO achieved 91.2% mAP@0.5 on the custom dataset.
  • The model has only 2.3 million parameters, a 23.6% reduction compared to the baseline.
  • Performance improved by 2.9% over the baseline model.
  • Demonstrated suitability for environments with significant illumination variation and small object detection challenges.

Conclusions:

  • GSA-YOLO offers a lightweight and efficient solution for on-site safety helmet detection in confined spaces.
  • The algorithm effectively handles illumination variations and detects small/occluded objects.
  • Contributes to reducing industrial safety accidents through improved worker safety monitoring.