Trupthi Rao

Global Academy of Technology

Papers

1

Total Citations

2

H-Index

1

About

Trupthi Rao is a rising researcher in the field of affective computing and deep learning, with a focused interest in enhancing computer-human interaction through emotion recognition. Their most notable contribution is the development of "EmoCNN," a customized Convolutional Neural Network architecture designed to precisely identify and classify human emotions. This work, published in 2024, systematically investigates the impact of different optimizers on model performance, offering a practical pathway to more responsive and intuitive AI systems. While still early in its trajectory, this foundational research has already garnered attention, accumulating 2 citations and establishing Rao as a promising voice in the intersection of computer vision and human psychology. By tackling the nuanced challenge of decoding human emotional states, Trupthi Rao is contributing to a future where machines can better understand and respond to the people they serve.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
EmoCNN: Unleashing Human Emotions with Customized CNN Using Different Optimizers
2 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Global Academy of Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago