Papers

6

Total Citations

157

H-Index

4

About

Mohana is a prolific researcher whose work sits at the intersection of computer vision, deep learning, and artificial intelligence, with particular expertise in graph neural networks, object detection, and intelligent surveillance systems. Perhaps her most influential contribution is her 2021 exploration of Graph Neural Networks — including GAT, GCN, and GRN architectures — applied to image and video understanding, a paper that has garnered 83 citations and established her as a notable voice in the GNN community. Complementing this, her work on 3D multi-object detection and tracking using deep learning (39 citations) has advanced understanding of autonomous systems and robotics applications. Her 2016 real-time DSP implementation of object detection for video surveillance (24 citations) demonstrates a long-standing commitment to practical, deployable AI solutions. More recently, Mohana has broadened her scope into healthcare AI and precision agriculture, investigating YOLOv5-based crop detection with edge computing and AI-driven modern healthcare systems. Her latest work on web-controlled surveillance robotics underscores her enduring passion for bridging theoretical AI research with real-world, safety-critical applications — making her scholarship both technically rigorous and meaningfully impactful.

Research Focus

Key Achievements

4
H-Index
6
Papers
157
Total Citations
26
Avg Citations/Paper
🏆 Most Cited Paper
Graph Neural Network (GNN) in Image and Video Understanding Using Deep Learning for Computer Vision Applications
83 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: R.V. College of Engineering

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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