Rupesh Konduru
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Research Areas
Biography and Research Information
OverviewAI-generated summary
Rupesh Konduru's research focuses on advancements in machine learning applications for computer vision tasks, particularly in object detection and image segmentation. His recent publications explore the use of transformer architectures and customized loss functions to optimize multi-class label detection and bounding box regression. He has also investigated the application of convolutional neural networks (CNNs) for multi-modal perception in robotic manipulation, specifically within automotive repair contexts. Additionally, Konduru's work includes developing improved topological image processing techniques for skin lesion segmentation. He has one shared publication with collaborator Hong Cheng from Southern Arkansas University.
Metrics
- h-index: 1
- Publications: 2
- Citations: 2
Selected Publications
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Skin Lesion Segmentation Using Improved Topological Image Processing (2025)
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Multi-Class Label Detection and Bounding Box Regression Using Transformer with a Customized Loss Function (2024)
Collaboration Network
Top Collaborators
- Multi-Class Label Detection and Bounding Box Regression Using Transformer with a Customized Loss Function
- Skin Lesion Segmentation Using Improved Topological Image Processing
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