arXiv (All)
open access
Silicon nitride nanophotonics for low-redundancy 3D convolution
Three-dimensional (3D) convolution extracts correlations in high-dimensional data, but overlapping receptive fields introduce substantial redundant data movement. Here, we demonstrate a silicon nitride 3D optical convolution accelerator (3D-OCA) that reconstructs receptive fields through coordinate-
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- All-optical doubly resonant cavities for energy-efficient ReLU function in nanophotonic deep learning.#292206
- Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing#19788
- Bimanual 3D Hand Motion and Articulation Forecasting in Everyday Images#1048509
- GoDeep: Annotation-Free Open-Vocabulary 3D Scene Understanding via Language-Space Lifting#986685
- Neuromorphic vision with quasi-BICs.#480895
Record · ID 1141290
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive