Class Incremental Learning in Efficient Job Task Recognition

Vaidegi K; Yogesh G; Vimalraj K; Yuvaraj R

Class Incremental Learning in Efficient Job Task Recognition

Author : Vaidegi K, Yogesh G, Vimalraj K, Yuvaraj R Journa Name: International Journal of Science, Engineering and Technology Volume: 14 issue: 2 Year: Volume-14-issue-2 Views : 170

Abstract:

The project titled “Class Incremental Learning in Efficient Job Task Recognition”focuses on developing an intelligent system capable of identifying and classifying job-related tasksusing machine learning techniques. The system utilizes advanced algorithms to analyze input dataand categorize tasks into predefined classes with high accuracy. A key feature of the proposedsystem is its ability to support incremental learning, allowing new job categories to be addedwithout retraining the entire model. This improves scalability and efficiency in dynamicenvironments where new tasks frequently emerge. The system integrates datapreprocessing,feature extraction, and classification modules to ensure reliable performance. Experimental resultsdemonstrate improved accuracy and reduced computational cost compared to traditionalapproaches. The proposed solution is suitable for real-time applications and enhances automationin job task recognition systems.