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Title: The Temporal Robustness of Classification Algorithms: Investigating the Impact of Temporal Changes on Model Performance
Authors: Muhammad Sajid , Sadia Latif, Rana Muhammad Nadeem, Aafia Latif, Muhammad Hassnain Azhar
Journal: Kashf Journal of Multidisciplinary Research (KJMR)
| Category | From | To |
|---|---|---|
| Y | 2024-10-01 | 2025-12-31 |
Publisher: Kashf Institute of Development & Studies
Country: Pakistan
Year: 2025
Volume: 2
Issue: 3
Language: en
DOI: 10.71146/kjmr350
Keywords: Artificial Neural Network (ANN)Support Vector Machine (SVM)Digital Image Processing (DIP)License Plate Recognition (LPR)Template Matching (TM)
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.
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