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

Prosopagnosia

Prosopagnosia

Prosopagnosia, also known as face blindness, is the inability to recognize faces. In severe cases, individuals with prosopagnosia may not recognize close family members, including parents and spouses, by their faces. For instance, someone with prosopagnosia might walk past their child in a crowd, only realizing their mistake upon noticing their child's distinctive backpack or favorite jacket. Prosopagnosia specifically impairs facial recognition, while the recognition of other objects or...

You might also read

Related Articles

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

Sort by

Same author

Correction to: SIRT3 activation protects from nabumetone-induced mitochondrial toxicity in adult human cardiomyocytes.

Cellular and molecular life sciences : CMLS·2026

Same author

The cGAS-STING pathway contributes to cisplatin-induced skeletal muscle atrophy through altered proteostasis and myogenic signaling.

Cell communication and signaling : CCS·2026

Same author

CsWRKY6-2/CsWRKY12 module regulates gallated catechin biosynthesis in tea plants.

The Plant journal : for cell and molecular biology·2026

Same author

De Novo Design of Near-Infrared Fluorescence-Activating Proteins.

Journal of the American Chemical Society·2026

Same author

The impact of accelerated 40 Hz transcranial alternating current stimulation on sleep in patients with major depressive disorder: A secondary analysis of a randomized controlled trial.

Journal of affective disorders·2026

Same author

Thrombopoietin Receptor MPL in Hematopoiesis and Myeloproliferative Neoplasms: Physiological Roles and Pathogenic Mechanisms.

Stem cell reviews and reports·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

Search research articles

Related Experiment Video

Updated: Jul 12, 2025

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Published on: March 17, 2023

Scene Uyghur Recognition Based on Visual Prediction Enhancement.

Yaqi Liu^1,2,3, Fanjie Kong^1,2,3, Miaomiao Xu^1,2,3

¹College of Information Science and Engineering, Xinjang University, No. 777 Huarui Street, Urumqi 830017, China.

Sensors (Basel, Switzerland)

|October 28, 2023

Summary

This summary is machine-generated.

This study introduces an improved scene Uyghur recognition model to address text deformation and character similarity issues. The enhanced model achieves more accurate visual predictions for Uyghur text in complex scene images.

Keywords:

Uyghur recognition correction network scene Uyghur dataset scene text recognition vision model

More Related Videos

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

Related Experiment Videos

Last Updated: Jul 12, 2025

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Published on: March 17, 2023

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

Area of Science:

Computer Vision
Natural Language Processing
Optical Character Recognition

Background:

Scene text recognition faces challenges with Uyghur text, including oblique deformation, character adhesion, and similarity.
Existing methods struggle to accurately recognize Uyghur characters in diverse and complex image conditions.

Purpose of the Study:

To develop an enhanced scene Uyghur recognition model with improved visual prediction capabilities.
To address specific issues of skewed text, character adhesion, and similar character differentiation in Uyghur scene text.

Main Methods:

Utilized TPS++ for feature-level correction of skewed text.
Improved the U-Net structure within ABINet to aggregate horizontal features and enhance spatial characterization.
Introduced a visual masking semantic awareness (VMSA) module to integrate language information for better visual prediction.

Main Results:

The proposed model effectively handles oblique deformation and character adhesion in Uyghur text.
The VMSA module aids in distinguishing between visually similar Uyghur characters by leveraging language context.
Ablation experiments validated the effectiveness of the individual components and the overall model.

Conclusions:

The enhanced scene Uyghur recognition model demonstrates superior performance compared to existing methods on a custom dataset.
The integration of visual and semantic information through the VMSA module is crucial for accurate Uyghur scene text recognition.