4 papers
Memory-efficient optimization of implicit neural representations for CT reconstruction
Mahrokh Najaf, Gregory Ongie
Implicit neural representations (INRs) provide a parameter-efficient and fully differentiable image model for CT reconstruction. However, optimizing INRs for CT reconstruction usin…
Sampling Theory for Super-Resolution with Implicit Neural Representations
Mahrokh Najaf, Gregory Ongie
Implicit neural representations (INRs) have emerged as a powerful tool for solving inverse problems in computer vision and computational imaging. INRs represent images as continuou…
Towards a Sampling Theory for Implicit Neural Representations
Mahrokh Najaf, Gregory Ongie
Implicit neural representations (INRs) have emerged as a powerful tool for solving inverse problems in computer vision and computational imaging. INRs represent images as continuou…
Accelerated Optimization of Implicit Neural Representations for CT Reconstruction
Mahrokh Najaf, Gregory Ongie
Inspired by their success in solving challenging inverse problems in computer vision, implicit neural representations (INRs) have been recently proposed for reconstruction in low-d…