Design, train and generate neural networks optimized specifically for FPGAs.

artifical-intelligence deep-learning embedded-systems fpga
4 Open Issues Need Help Last updated: Aug 27, 2025

Open Issues Need Help

View All on GitHub

AI Summary: This issue proposes to fully define the semantics and potential constraints for fields within `meta.toml` files used for plugins. The goal is to ensure clarity and consistency by specifying exact meanings, evaluating the necessity of existing fields, and defining allowed values for certain fields.

Complexity: 3/5
enhancement help wanted major priority concept discussion

Design, train and generate neural networks optimized specifically for FPGAs.

Python
#artifical-intelligence#deep-learning#embedded-systems#fpga

Design, train and generate neural networks optimized specifically for FPGAs.

Python
#artifical-intelligence#deep-learning#embedded-systems#fpga
good first issue minor priority refactor

Design, train and generate neural networks optimized specifically for FPGAs.

Python
#artifical-intelligence#deep-learning#embedded-systems#fpga
good first issue medium priority refactor

Design, train and generate neural networks optimized specifically for FPGAs.

Python
#artifical-intelligence#deep-learning#embedded-systems#fpga