Deep Learning with Work Patterns-Based Remote Work Productivity Analyzer
Authors:
M. V. S. Aditya, M. V.V. S. Siddhartha Reddy, S. Ganesh Chary, Mrs. G. Priyanka
Page No: 1046-1055
Abstract:
Remote work has become an integral part of modern workplaces, driven by advancements in digital communication and accelerated by global events. While remote work offers flexibility and efficiency, organizations face challenges in objectively measuring employee productivity beyond conventional time-tracking mechanisms. The study presents a Deep Learning-based Remote Work Productivity Analyzer that leverages work patterns to assess and predict employee productivity.
Description:
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Volume & Issue
Volume-14,Issue-4
Keywords
Remote work, Productivity, Deep Learning, Work patterns, Machine learning, Collaboration metrics, Behaviouralpatterns, Time-tracking, Performance evaluation, Employee efficiency, Work activity data, Engagement levels, Task execution efficiency,