Subhadipto Poddar
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Also affiliated: Iowa State University (2018–2022); Oklahoma Department of Human Services (2020)
Research Areas
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Biography and Research Information
OverviewAI-generated summary
Subhadipto Poddar's research focuses on the application of advanced computational methods, particularly deep learning and data-driven approaches, to address challenges in transportation safety and infrastructure inspection. His work investigates the use of video analytics for improving traffic intersection safety and performance, as well as for identifying and classifying traffic congestion. Poddar has also explored the impact of COVID-19 on traffic signal systems and pedestrian activity. His recent publications include studies on deep learning-based object detection for unmanned aerial systems (UASs) in construction stormwater practice inspections and real-time barge detection using traffic cameras and deep learning on inland waterways. He has collaborated with researchers Sarah Hernandez and Maria Falquez at the University of Arkansas at Fayetteville on multiple projects.
Metrics
- h-index: 7
- Publications: 20
- Citations: 268
Positions
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Graduate Research Assistant 2016–2020Iowa State University Institute of Transportation ORCID
Selected Publications
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Real-Time Barge Detection Using Traffic Cameras and Deep Learning on Inland Waterways (2024)
Collaboration Network
Top Collaborators
- Real-Time Barge Detection Using Traffic Cameras and Deep Learning on Inland Waterways
- Real-Time Barge Detection Using Traffic Cameras and Deep Learning on Inland Waterways
- Real-Time Barge Detection Using Traffic Cameras and Deep Learning on Inland Waterways
- Real-Time Barge Detection Using Traffic Cameras and Deep Learning on Inland Waterways
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