Jove
Visualize
Contact Us

Related Concept Videos

Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

6.7K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
6.7K
Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

2.0K
When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
Different compounds display unique properties due to their...
2.0K
Light Acquisition02:16

Light Acquisition

8.5K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.5K
IR Spectrometers01:25

IR Spectrometers

1.2K
There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
1.2K
Detection of Black Holes01:10

Detection of Black Holes

2.2K
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...
2.2K
Gas Chromatography: Types of Detectors-II01:19

Gas Chromatography: Types of Detectors-II

442
In gas chromatography, different detectors are employed to meet specific analytical needs. These detectors are often categorized based on their detection mechanisms and the types of compounds they are best suited to analyze. Thermal Conductivity Detectors (TCD), Flame Ionization Detectors (FID), and Electron Capture Detectors (ECD) represent common categories, each with unique operating principles and applications. However, beyond these, several other detectors are designed for more specialized...
442

You might also read

Related Articles

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

Sort by
Same author

Psychological Impact and Workload of COVID-19 on Healthcare Workers in China During the Early Time of the Pandemic: A Cross-sectional Study.

Disaster medicine and public health preparedness·2022
Same author

Manipulation of Band Alignment in Two-Dimensional Vertical WSe<sub>2</sub>/BA<sub>2</sub>PbI<sub>4</sub> Ruddlesden-Popper Perovskite Heterojunctions via Defect Engineering.

The journal of physical chemistry letters·2022
Same author

Efficient and Stable Perovskite Solar Cells via CsPF<sub>6</sub> Passivation of Perovskite Film Defects.

The journal of physical chemistry letters·2022
Same author

Development of an Indirect ELISA Kit for Rapid Detection of Varicella-Zoster Virus Antibody by Glycoprotein E.

Frontiers in microbiology·2022
Same author

Adhesive Materials Inspired by Barnacle Underwater Adhesion: Biological Principles and Biomimetic Designs.

Frontiers in bioengineering and biotechnology·2022
Same author

Protective effect of cinnamaldehyde on channel catfish infected by drug-resistant Aeromonas hydrophila.

Microbial pathogenesis·2022
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: Aug 2, 2025

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

7.8K

Improved YOLOv5 infrared tank target detection method under ground background.

Chao Liang1,2, Zhengang Yan3, Meng Ren3

  • 1School of Artificial Intelligence, Xidian University, Xi'an, 710071, China. 1025743995@qq.com.

Scientific Reports
|April 17, 2023
PubMed
Summary

This study introduces a novel YOLOv5s-THSE model to enhance infrared tank detection accuracy. The improved model effectively suppresses complex backgrounds and boosts detection performance for ground targets.

More Related Videos

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
10:42

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

Published on: March 22, 2019

6.3K
Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
10:56

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Published on: March 6, 2014

12.6K

Related Experiment Videos

Last Updated: Aug 2, 2025

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

7.8K
Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
10:42

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

Published on: March 22, 2019

6.3K
Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
10:56

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Published on: March 6, 2014

12.6K

Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Infrared Imaging Technology

Background:

  • Infrared seeker detection precision is crucial for guidance systems.
  • Challenges in detecting ground tank targets include scale variations, complex backgrounds, and subtle infrared characteristics.
  • Existing methods struggle with low target detection accuracy in challenging infrared imaging scenarios.

Purpose of the Study:

  • To develop an advanced You Only Look Once, Transform Head Squeeze-and-Excitation (YOLOv5s-THSE) model for improved infrared tank detection.
  • To enhance the extraction of target features and suppress complex ground backgrounds.
  • To increase the accuracy and stability of detecting small and inconspicuous infrared targets.

Main Methods:

  • Integration of a multi-head attention mechanism into the backbone and neck of the YOLOv5s network.
  • Incorporation of a Cross Stage Partial, Squeeze-and-Exclusion module in the network's neck.
  • Introduction of a small object detection head and utilization of the CIoU loss function.

Main Results:

  • The proposed YOLOv5s-THSE model demonstrates superior performance in detecting infrared tank targets against complex ground backgrounds.
  • Effective suppression of background noise and enhanced focus on target features were achieved.
  • Significant improvements in detection accuracy and training stability were observed compared to baseline YOLOv5s and other variants.

Conclusions:

  • The YOLOv5s-THSE model offers a robust solution for enhancing infrared tank detection capabilities.
  • The applied attention mechanisms and specialized modules effectively address challenges posed by complex environments.
  • This research contributes to advancing the precision of infrared guidance systems through improved target recognition.