GitHub / LaErre9 / Zynq_Ultrascale_Vitis_AI_CNN_ZCU102
Workflow for Executing CNN Networks on Zynq Ultrascale+ with VITIS AI. Detailed analysis, configuration, and execution of Convolutional Neural Networks on ZCU102 using VITIS AI, evaluating performance on the board compared to Cloud infrastructure. Developed for educational exam purposes.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LaErre9%2FZynq_Ultrascale_Vitis_AI_CNN_ZCU102
PURL: pkg:github/LaErre9/Zynq_Ultrascale_Vitis_AI_CNN_ZCU102
Stars: 16
Forks: 2
Open issues: 0
License: gpl-3.0
Language: Jupyter Notebook
Size: 252 MB
Dependencies parsed at: Pending
Created at: about 2 years ago
Updated at: 4 months ago
Pushed at: over 1 year ago
Last synced at: 8 days ago
Topics: ai-embedded-systems, deep-learning-processor-unit, dpu, mpsoc, petalinux, traffic-sign-recognition, vitis-ai, vivado, zcu102, zynq-ultrascale