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

Association Areas of the Cortex01:21

Association Areas of the Cortex

10.8K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
10.8K
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

2.4K
IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
2.4K

You might also read

Related Articles

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

Sort by
Same author

Dissecting T-cell exhaustion heterogeneity and immune ecosystem dynamics in colorectal cancer through multi-omics machine learning.

BMC cancer·2026
Same author

Clinical Features of Cellular Senescence Pathways in Severe Asthma.

Allergy·2026
Same author

The RNA-binding protein RBFOX2 suppresses colorectal cancer proliferation and metastasis by reducing FUBP1 mRNA stability to induce mitochondrial dysfunction and ferroptosis.

Discover oncology·2026
Same author

Hemin-amino acid co-assembly nanozymes with dual enzyme-mimicking activities for <i>in situ</i> oxygen generation-enhanced one-step biosensing of glucose and H<sub>2</sub>O<sub>2</sub>.

RSC advances·2026
Same author

Hybrid Curriculum Learning for Data-Efficient Lung Nodule Detection with YOLOv11.

Diagnostics (Basel, Switzerland)·2026
Same author

Oral Bioinspired Peroxisome-Engineered Probiotics for Modulating Gut Microbiota Homeostasis and Alleviating Cardiac Chemotherapy Toxicity.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Apr 18, 2026

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

1.3K

Fast traffic sign recognition with a rotation invariant binary pattern based feature.

Shouyi Yin1, Peng Ouyang2, Leibo Liu3

  • 1Institute of Microelectronics, Tsinghua University, Beijing 100084, China. yinsy@tsinghua.edu.cn.

Sensors (Basel, Switzerland)
|January 22, 2015
PubMed
Summary
This summary is machine-generated.

This study presents a fast and robust traffic sign recognition method for driving safety. It uses Hough transformation, Rotation Invariant Binary Patterns, and Artificial Neural Networks for improved detection and recognition speed.

Related Experiment Videos

Last Updated: Apr 18, 2026

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

1.3K

Area of Science:

  • Computer Vision
  • Machine Learning
  • Automotive Safety

Background:

  • Traffic sign recognition is crucial for advanced driver-assistance systems (ADAS).
  • Existing methods face challenges in speed and robustness against variations in scale, rotation, and illumination.

Purpose of the Study:

  • To develop a fast and robust traffic sign recognition system.
  • To enhance driving safety through improved traffic sign detection and recognition.

Main Methods:

  • Utilized Hough transformation for initial candidate region localization.
  • Introduced Rotation Invariant Binary Patterns (RIBPs) in affine and Gaussian spaces for scale, rotation, and illumination invariance.
  • Employed Artificial Neural Networks (ANNs) for feature dimension reduction and classification to accelerate recognition.

Main Results:

  • Achieved robust traffic sign recognition across various conditions.
  • Demonstrated comparable recognition accuracy to existing methods.
  • Showcased significantly faster processing speeds, including training and recognition.

Conclusions:

  • The proposed method offers a robust and efficient solution for traffic sign recognition.
  • This advancement contributes to the development of safer and more reliable driving assistance systems.