@article {10.3844/jcssp.2025.1819.1833,
article_type = {journal},
title = {Person Re-Identification From Video Surveillance Systems Using Artificial Intelligence Methods},
author = {Baggam, Revathi Lavanya and Kumari, Vatsavayi Valli},
volume = {21},
number = {8},
year = {2025},
month = {Sep},
pages = {1819-1833},
doi = {10.3844/jcssp.2025.1819.1833},
url = {https://thescipub.com/abstract/jcssp.2025.1819.1833},
abstract = {The study explores use of deep learning models in person re identification, leveraging the advancements made in face recognition however the abundance of model choices presents a challenge in selecting the optimal architecture. The study proposes a comprehensive framework for evaluating deep learning models on person re-identification tasks by considering various performance metrics, dataset preprocessing methods, model architectures, and evaluation techniques to enable a systematic comparison of different approaches through empirical analyses on standard person re-identification datasets. The proposed framework is worked-out in uncovering the strengths and limitations of diverse deep learning strategies. The primary objective is to utilize face recognition methodologies to achieve accurate person re-identification.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}