XAli-SHX/FPGA-Implementation-of-Image-Processing-for-MNIST-Dataset-Based-on-CNN-Algorithm
FPGA Implementation of Image Processing for MNIST Dataset Based on Convolutional Neural Network Algorithm (CNN)
This project helps embedded systems engineers and hardware designers implement image processing tasks on FPGAs. It takes a pre-trained Convolutional Neural Network (CNN) model designed for the MNIST dataset and translates it into a hardware description. The output is a synthesizable FPGA design that can rapidly classify handwritten digits.
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Use this if you need to accelerate handwritten digit recognition by implementing a CNN on an FPGA for high-speed, low-power inference.
Not ideal if you are looking for a software-only solution or need to train a new machine learning model, as this focuses on hardware implementation of an existing model.
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VHDL
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Last pushed
Dec 12, 2023
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