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

Ranks

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...

You might also read

Related Articles

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

Sort by

Same author

Reply to Yu et al.

Endoscopy·2026

Same author

A rural-to-center artificial intelligence model for diagnosing Helicobacter pylori infection and premalignant gastric conditions using endoscopy images captured in routine practice.

Endoscopy·2025

Same author

Real-Time Identification of Cricothyrotomy Landmarks in Emergency Care and Obstetric Patients Using Wireless Handheld Ultrasound and Edge-Computing Artificial Intelligence: A Prospective Observational Study.

Journal of medical systems·2025

Same author

A framework for integrating genomics, microbial traits, and ecosystem biogeochemistry.

Nature communications·2025

Same author

Application of Machine Learning to Ultrasonography in Identifying Anatomical Landmarks for Cricothyroidotomy Among Female Adults: A Multi-center Prospective Observational Study.

Journal of imaging informatics in medicine·2024

Same author

Towards Adversarial Robustness for Multi-Mode Data through Metric Learning.

Sensors (Basel, Switzerland)·2023

Search research articles

Related Experiment Video

Updated: Apr 18, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

A learning framework for age rank estimation based on face images with scattering transform.

Kuang-Yu Chang, Chu-Song Chen

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|January 11, 2015

Summary

This summary is machine-generated.

This study introduces a novel cost-sensitive ordinal hyperplanes algorithm for accurate human age estimation from facial images. The method improves ranking by considering relative age order and optimizing binary classifiers, outperforming existing techniques.

More Related Videos

Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting

Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting

Published on: March 25, 2019

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Apr 18, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting

Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting

Published on: March 25, 2019

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Area of Science:

Computer Vision
Machine Learning
Biometrics

Background:

Accurate human age estimation from facial images is crucial for various applications.
Existing methods often struggle with the ordinal nature of age and cost-sensitive misclassifications.

Purpose of the Study:

To develop a cost-sensitive ordinal hyperplanes ranking algorithm for improved human age estimation.
To introduce a novel facial feature descriptor for enhanced age inference.

Main Methods:

Exploiting relative-order information among age labels for rank prediction.
Aggregating binary classification results with introduced cost sensitivities for performance improvement.
Utilizing a scattering transform descriptor for facial feature extraction, generalizing conventional bio-inspired features.

Main Results:

The proposed algorithm effectively estimates human age from face images.
The scattering transform descriptor proves more effective for face-based age inference.
Experimental results show superior performance compared to state-of-the-art age estimation methods.

Conclusions:

The cost-sensitive ordinal hyperplanes approach offers a robust framework for age estimation.
The scattering transform is a powerful feature for facial analysis and age inference.
This work advances the field of automated human age estimation.