Work

The Temporal Robustness of Classification Algorithms: Investigating the Impact of Temporal Changes on Model Performance

Year: 2025

Type: article

Abstract: Classifiers are the main source of processing of identification application task, So the performance of classifiers effect the work of any application. In this paper, author is working in the Digital Image Processing (DIP) domain, In License Plate Recognition (LPR) application of it. The purpose of this paper is, to introduce systemic literature review on why classification algorithms don’t work effectively after some period of time in some countries. Which decrease the performance of classifiers while processing License Plate Recognition (LPR) application or any identification application. Recognition of characters in any identification system take most important than other steps.

Source: Kashf Journal of Multidisciplinary Research

DOI: 10.71146/kjmr350

Authors: Muhammad Sajid, Sadia Latif, Rana Muhammad Nadeem, Aafia Latif, Muhammad Hassnain Azhar

Institutions: National College of Business Administration and Economics, Bahauddin Zakariya University, Institute of Southern Punjab

Language: English

Topic: Vehicle License Plate Recognition

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4409319208

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Cites: 20

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Related to: 10