all AI news
Configurable Learned Holography
May 6, 2024, 4:42 a.m. | Yicheng Zhan, Liang Shi, Wojciech Matusik, Qi Sun, Kaan Ak\c{s}it
cs.LG updates on arXiv.org arxiv.org
Abstract: In the pursuit of advancing holographic display technology, we face a unique yet persistent roadblock: the inflexibility of learned holography in adapting to various hardware configurations.
This is due to the variances in the complex optical components and system settings in existing holographic displays.
Although the emerging learned approaches have enabled rapid and high-quality hologram generation, any alteration in display hardware still requires a retraining of the model.
Our work introduces a configurable learned model …
abstract arxiv components cs.cv cs.gr cs.lg display technology eess.iv face hardware optical physics.optics technology type unique
More from arxiv.org / cs.LG updates on arXiv.org
Efficient Data-Driven MPC for Demand Response of Commercial Buildings
2 days, 14 hours ago |
arxiv.org
Testing the Segment Anything Model on radiology data
2 days, 14 hours ago |
arxiv.org
Calorimeter shower superresolution
2 days, 14 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US