Research on person re-identification algorithm based on multi-task learning
Person re-identification (re-ID) involves the cross-camera retrieval and matching of target pedestrian images, facilitating pedestrian association in scenarios where biometric features such as faces and fingerprints may prove ineffective. It has become a
MI Rongxin, YAO Wenwen, WU Binghao
doaj
Patient Identification Based on Deep Metric Learning for Preventing Human Errors in Follow-up X-Ray Examinations. [PDF]
Ueda Y, Morishita J.
europepmc +1 more source
Objective We developed a novel EHR sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk +16 more
wiley +1 more source
Opportunistic screening of type 2 diabetes with deep metric learning using electronic health records. [PDF]
Jin Q +14 more
europepmc +1 more source
Leaf disease image retrieval with object detection and deep metric learning. [PDF]
Peng Y, Wang Y.
europepmc +1 more source
Retractions in rheumatology: trends, causes, and implications for research integrity
Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley +1 more source
Deep Metric Learning-Based Classification for Pavement Distress Images. [PDF]
Li Y, Wang J, Lü B, Yang H, Wu X.
europepmc +1 more source
A cross-modal deep metric learning model for disease diagnosis based on chest x-ray images. [PDF]
Jin Y, Lu H, Li Z, Wang Y.
europepmc +1 more source
Ghost Echoes Revealed: Benchmarking Maintainability Metrics and Machine Learning Predictions Against Human Assessments [PDF]
Markus Borg +2 more
openalex +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source

