Kalpna Guleria
Papers
3
Total Citations
26
H-Index
3
About
Kalpna Guleria is a researcher whose work sits at the intersection of intelligent automation and agricultural technology. Her primary research areas include Robotic Process Automation (RPA) for service optimization and deep learning for precision agriculture. Guleria’s major contributions are twofold: she has pioneered the application of RPA in the tourism sector, developing a framework for hotel inventory control systems for online travel agencies that automates repetitive tasks, thereby enhancing operational efficiency. More recently, she has focused on food security, leveraging pre-trained deep learning models, specifically the EfficientNet architecture, to detect diseases in cassava leaves—a critical staple crop. Her work in this area, detailed in two key papers from 2023 and 2024, demonstrates how advanced computer vision can empower farmers to boost crop yields. With her most cited paper, "A Framework for Hotel Inventory Control System for Online Travel Agency using Robotic Process Automation," accumulating 17 citations, Guleria’s research is gaining traction for its practical, cross-sector impact. By bridging the gap between service automation and sustainable agriculture, she is shaping a future where AI-driven solutions address both economic and environmental challenges.
Research Focus
Key Achievements
Top Papers
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