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Distilled Roads: Generalisable Road Network Extraction Across Sensors, Resolutions, and Region
Sanayya, Rakshith Sathish, Ashwathi Nambiar
Road network segmentation from satellite imagery remains challenging due to large geographic variation in road appearance, occlusions, and domain shifts introduced by differing res…
SAModified: A Foundation Model-Based Zero-Shot Approach for Refining Noisy Land-Use Land-Cover Maps
Sparsh Pekhale, Rakshith Sathish, Sathisha Basavaraju +1
Land-use and land cover (LULC) analysis is critical in remote sensing, with wide-ranging applications across diverse fields such as agriculture, utilities, and urban planning. Howe…
Exploiting Richness of Learned Compressed Representation of Images for Semantic Segmentation
Ravi Kakaiya, Rakshith Sathish, Ramanathan Sethuraman +1
Autonomous vehicles and Advanced Driving Assistance Systems (ADAS) have the potential to radically change the way we travel. Many such vehicles currently rely on segmentation and o…
Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks
Rakshith Sathish, Swanand Khare, Debdoot Sheet
Convolutional Neural Networks have played a significant role in various medical imaging tasks like classification and segmentation. They provide state-of-the-art performance compar…