arXiv (All)
open access
PrototypeNAS: Rapid Design of Deep Neural Networks for Microcontroller Units
Enabling efficient deep neural network (DNN) inference on edge devices with different hardware constraints is a challenging task that typically requires DNN architectures to be specialized for each device separately. To avoid the huge manual effort, one can use neural architecture search (NAS). Howe
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
- Official Review · ICLR 2025#787197
- REQAP: Resilient Weight Packing and Quantization for Edge DNN Acceleration#1011289
- A Survey on Evolutionary Construction of Deep Neural Networks#19809
- Classification of Real and Fake Human Faces Using Deep Learning#94470
- Structure Aware Neural Architecture Search for Mixture of Experts#798441
Record · ID 1130515
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