5 papers
Beyond Bayer: Task-Optimal Sensor Co-Design for Robust Autonomous-Driving Segmentation
Reeshad Khan, John Gauch
Robust perception underpins autonomous driving, and most recent progress comes from scaling the model-larger backbones, foundation models, and cooperative multi-agent fusion. We pu…
Learning to Sense for Driving: Joint Optics-Sensor-Model Co-Design for Semantic Segmentation
Reeshad Khan, John Gauch
Traditional autonomous driving pipelines decouple camera design from downstream perception, relying on fixed optics and handcrafted ISPs that prioritize human viewable imagery rath…
TinyBEV: Cross Modal Knowledge Distillation for Efficient Multi Task Bird's Eye View Perception and Planning
Reeshad Khan, John Gauch
We present TinyBEV, a unified, camera only Bird's Eye View (BEV) framework that distills the full-stack capabilities of a large planning-oriented teacher (UniAD [19]) into a compac…
Adaptive Extensions of Unbiased Risk Estimators for Unsupervised Magnetic Resonance Image Denoising
Reeshad Khan, John Gauch, Ukash Nakarmi
The application of Deep Neural Networks (DNNs) to image denoising has notably challenged traditional denoising methods, particularly within complex noise scenarios prevalent in med…
OrthoNets: Orthogonal Channel Attention Networks
Hadi Salman, Caleb Parks, Matthew Swan +1
Designing an effective channel attention mechanism implores one to find a lossy-compression method allowing for optimal feature representation. Despite recent progress in the area,…