FPGA Image Quality Evaluation with ML

I'm working on a project that involves evaluating image quality using machine learning on an FPGA. Key Requirements: - The primary goal of this project is to achieve highly accurate results in image quality. - The images I'll be evaluating are mostly photographs. - I'm looking to implement a Convolutional Neural Network (CNN) model for this project. Key Skills/Experience needed: - Proficiency with FPGA development, particularly with VIVADO. - Strong background in image processing and machine learning. - Previous experience with implementing CNN models on FPGA for image quality evaluations would be a great plus. If you're confident in your FPGA skills, have a background in image processing and ML, and have worked with CNN models, I'm eager to hear from you.