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

X-ray Imaging01:24

X-ray Imaging

5.5K
German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
5.5K
Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

188
The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...
188
Ultrasonography01:17

Ultrasonography

4.5K
Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called...
4.5K

You might also read

Related Articles

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

Sort by
Same author

Mechanisms of energy metabolism reprogramming and homeostasis maintenance in overwintering hibernating animals.

Frontiers in veterinary science·2026
Same author

[Metabolic engineering of <i>Escherichia coli</i> for efficient production of nicotinamide riboside].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology·2026
Same author

Focusing on vulnerable populations in HIV.

Chinese medical journal·2026
Same author

Regulation of amylose content in dialdehyde starches for crosslinking with gelatin Schiff base hydrogels: tunable network architecture for strength-toughness balanced hydrogels.

Food chemistry·2026
Same author

LSM7 coordinates scaRNA-mediated snRNA modification to ensure spliceosome fidelity and spermatogonial stem cell differentiation.

Cell death and differentiation·2026
Same author

Metabolic reprogramming and mitochondrial dynamics: Novel therapeutic perspectives for age-related macular degeneration.

Experimental eye research·2026

Related Experiment Video

Updated: Jul 3, 2025

High Spatial Resolution Chemical Imaging of Implant-Associated Infections with X-ray Excited Luminescence Chemical Imaging Through Tissue
07:48

High Spatial Resolution Chemical Imaging of Implant-Associated Infections with X-ray Excited Luminescence Chemical Imaging Through Tissue

Published on: September 30, 2022

1.3K

Lightweight Detection Method for X-ray Security Inspection with Occlusion.

Zanshi Wang1, Xiaohua Wang1, Yueting Shi2

  • 1School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China.

Sensors (Basel, Switzerland)
|February 10, 2024
PubMed
Summary
This summary is machine-generated.

This study enhances YOLOv8 for X-ray security inspections, improving prohibited item detection accuracy by incorporating adaptive spatial feature fusion and coordinate attention. The modified model shows significant gains in mean average precision across various test sets.

Keywords:
X-ray security inspectionYOLOv8deep learninglightweight modelobject detection

More Related Videos

Handheld Metal Detector Screening for Metallic Foreign Body Ingestion in Children
04:55

Handheld Metal Detector Screening for Metallic Foreign Body Ingestion in Children

Published on: September 11, 2018

10.8K
Wideband Optical Detector of Ultrasound for Medical Imaging Applications
08:21

Wideband Optical Detector of Ultrasound for Medical Imaging Applications

Published on: May 11, 2014

11.3K

Related Experiment Videos

Last Updated: Jul 3, 2025

High Spatial Resolution Chemical Imaging of Implant-Associated Infections with X-ray Excited Luminescence Chemical Imaging Through Tissue
07:48

High Spatial Resolution Chemical Imaging of Implant-Associated Infections with X-ray Excited Luminescence Chemical Imaging Through Tissue

Published on: September 30, 2022

1.3K
Handheld Metal Detector Screening for Metallic Foreign Body Ingestion in Children
04:55

Handheld Metal Detector Screening for Metallic Foreign Body Ingestion in Children

Published on: September 11, 2018

10.8K
Wideband Optical Detector of Ultrasound for Medical Imaging Applications
08:21

Wideband Optical Detector of Ultrasound for Medical Imaging Applications

Published on: May 11, 2014

11.3K

Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Security Technology

Background:

  • X-ray security inspections face challenges in detecting prohibited items due to insufficient feature extraction, sample imbalance, and occlusions.
  • Existing object detection methods struggle with accuracy in complex security imaging scenarios.

Purpose of the Study:

  • To improve the accuracy of prohibited item detection in X-ray security inspection images.
  • To develop an enhanced object detection model based on YOLOv8 that addresses limitations in feature extraction, sample imbalance, and occlusion.

Main Methods:

  • An object detection method based on YOLOv8 was proposed, integrating adaptive spatial feature fusion (ASFF) and weighted feature concatenation for enhanced scale feature extraction.
  • A coordinate attention module (CoordAtt) was embedded to improve the learning of relevant features.
  • A slide loss function was introduced to balance simple and difficult samples, and Soft-Non-Maximum Suppression (Soft-NMS) was used to handle occlusions.

Main Results:

  • The proposed YOLOv8n model achieved mean average precision (mAP) of 90.2% (Easy), 90.5% (Hard), 79.1% (Hidden), and 91.4% (SIXray).
  • Compared to the original model, the mAP increased by 2.7%, 3.1%, 9.3%, and 2.4% on the respective datasets.
  • The modified YOLOv8n model maintains a low parameter count of approximately 3 million.

Conclusions:

  • The proposed enhancements to YOLOv8 significantly improve the detection accuracy of prohibited items in X-ray images.
  • The integration of ASFF, CoordAtt, slide loss, and Soft-NMS effectively addresses challenges like feature extraction, sample imbalance, and occlusion.
  • The model offers a computationally efficient solution for advanced security inspection systems.