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

Masking and Demasking Agents

Masking and Demasking Agents

EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on...

Deindividuation

Deindividuation

Deindividuation is a form of social influence on an individual’s behavior such that the individual engages in unusual or non-normal behavior while in a group setting. Why? Because in these group settings, the individual no longer sees themselves as an individual anymore, disinhibiting their behavior and personal restraint.

Difference from Background: Limit of Detection

Difference from Background: Limit of Detection

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...

You might also read

Related Articles

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

Sort by

Same author

Multi-Level Collaborative Distillation Meets Global Workspace Model: A Unified Framework for OCIL.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

Elevated suspended particulate matter reorganises carbon fraction in mangrove ecosystems.

Marine environmental research·2026

Same author

Learning Prompt Adapters for Forgetting-Free Continual Image Super-Resolution.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

Overcoming Dual Incremental Challenges in Continual Person Search via Adapter and Prototype.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

ActPrompt: In-Domain Feature Adaptation via Action Cues for Video Temporal Grounding.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

Prompt Disentanglement via Language Guidance and Representation Alignment for Domain Generalization.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

CAFE: Cross-View Adaptive Fusion and Cluster Center Enhancement for Robust Multi-View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

Learning Shape Anchors for Holistic Indoor Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 18, 2026

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Published on: December 24, 2015

Isolating Interference Factors for Robust Cloth-Changing Person Re-Identification.

De Cheng, Yubo Li, Chaowei Fang

IEEE Transactions on Pattern Analysis and Machine Intelligence

|January 16, 2026

Summary

This summary is machine-generated.

This study introduces a new framework for Cloth-Changing Person Re-Identification (CC-ReID) that disentangles identity features from interference factors like clothing. The method enhances person recognition accuracy in surveillance systems by isolating identity information.

More Related Videos

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

Related Experiment Videos

Last Updated: Jan 18, 2026

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Published on: December 24, 2015

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

Area of Science:

Computer Vision
Artificial Intelligence
Machine Learning

Background:

Cloth-Changing Person Re-Identification (CC-ReID) is vital for surveillance and security.
Current CC-ReID methods struggle with interference factors like clothing, viewpoint, and actions, impacting identity feature extraction.
Robust identity feature extraction requires addressing these interference factors.

Purpose of the Study:

To propose a novel framework for CC-ReID that systematically disentangles interference factors from identity features.
To ensure the robustness and discriminative power of identity representations despite variations.
To improve the accuracy and reliability of person re-identification systems.

Main Methods:

A dual-stream identity feature learning framework with raw and cloth-isolated streams.
An adaptive cloth-irrelevant contrastive objective to handle clothing variations.
A Text-Driven Conditional Generative Adversarial Interference Disentanglement Network (T-CGAIDN) to suppress other interference factors.

Main Results:

The proposed framework significantly outperforms state-of-the-art approaches on public benchmarks.
The method effectively disentangles identity features from various interference factors.
Demonstrated improved robustness and discriminative power in identity representations.

Conclusions:

The novel framework effectively addresses the challenges in CC-ReID by disentangling interference factors.
The approach enhances the performance of person re-identification systems.
The proposed method offers a significant advancement in the field of CC-ReID.