A Deep Learning Framework for Person Re-Identification in Railway Surveillance Systems

shiva

doi:10.64643/ijirtv12i8-191576-459

January 19, 2026International Journal of Innovative Research in TechnologyOpen Access

A Deep Learning Framework for Person Re-Identification in Railway Surveillance Systems

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Key Points

The research aims to assess the effectiveness of a deep learning framework for person re-identification in railway surveillance systems.
Developed a deep learning model for image processing and recognition.
Applied the model in a simulated railway surveillance environment.
Evaluated performance metrics including accuracy and speed of identification.
Demonstrated improved accuracy in identifying individuals compared to traditional methods.
Achieved faster processing times, making real-time identification feasible.

Implication

Evaluates a deep learning framework for enhancing person re-identification in railway surveillance systems, highlighting its potential for improved security.

Abstract

Explore the article titled A Deep Learning Framework for Person Re-Identification in Railway Surveillance Systems from IJIRT Volume 12, Issue 8. This study evaluates the effectiveness of teaching programs on waste management knowledge among women.

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Cite This Study

shiva (2026) studied this question.

synapsesocial.com/papers/69eb0bc7553a5433e34b55a9 https://doi.org/10.64643/ijirtv12i8-191576-459

View Full Paper

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A Deep Learning Framework for Person Re-Identification in Railway Surveillance Systems

Key Points

Implication

Abstract

Discussion

Cite This Study

A Deep Learning Framework for Person Re-Identification in Railway Surveillance Systems

Key Points

Implication

Abstract

Discussion

Cite This Study

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