63 citations · 68 across the 5 of their papers we have counts for
7 papers
What Not to Erase: Saliency-Constrained Augmentation for Low-Resource Handwritten Character Recognition
Paraskevi Platanou, John Pavlopoulos
Optical Character Recognition (OCR) and handwritten character recognition (HCR) in low-resource historical material collections often rely on data augmentation, yet augmentation st…
Learning Traversability for Long Horizon Off-Road Navigation
Kasi Viswanath, Jason M. Gregory, Shaunak Kolhe +1
Autonomous navigation across large off-road environments remains a challenging problem. Onboard sensors perceive only the immediate surroundings, yet safe and efficient routes depe…
Trailblazer: Learning offroad costmaps for long range planning
Kasi Viswanath, Felix Sanchez, Timothy Overbye +2
Autonomous navigation in off-road environments remains a significant challenge in field robotics, particularly for Unmanned Ground Vehicles (UGVs) tasked with search and rescue, ex…
GO: The Great Outdoors Multimodal Dataset
Peng Jiang, Kasi Viswanath, Akhil Nagariya +8
The Great Outdoors (GO) dataset is a multi-modal annotated data resource aimed at advancing ground robotics research in unstructured environments. Existing off-road datasets often…
Reflectivity Is All You Need!: Advancing LiDAR Semantic Segmentation
Kasi Viswanath, Peng Jiang, Srikanth Saripalli
LiDAR semantic segmentation frameworks predominantly use geometry-based features to differentiate objects within a scan. Although these methods excel in scenarios with clear bounda…
Off-Road LiDAR Intensity Based Semantic Segmentation
Kasi Viswanath, Peng Jiang, Sujit PB +1
LiDAR is used in autonomous driving to provide 3D spatial information and enable accurate perception in off-road environments, aiding in obstacle detection, mapping, and path plann…
OFFSEG: A Semantic Segmentation Framework For Off-Road Driving
Kasi Viswanath, Kartikeya Singh, Peng Jiang +2
Off-road image semantic segmentation is challenging due to the presence of uneven terrains, unstructured class boundaries, irregular features and strong textures. These aspects aff…