padhi499/Image-Classification-using-CNN-on-FPGA
Project is about designing a Trained Neural Network on FPGA to classify an Image Input using CNN.
This project helps FPGA design engineers implement a pre-trained Convolutional Neural Network (CNN) directly onto an FPGA for image classification. You input an image, and the FPGA outputs its classified category using a hardware-accelerated deep learning model. It's designed for professionals working with embedded systems and custom hardware for real-time image processing.
164 stars. No commits in the last 6 months.
Use this if you need to perform rapid, hardware-accelerated image classification on an FPGA, leveraging a pre-trained CNN model.
Not ideal if you're looking for a software-only solution for image classification or a tool to train new neural networks.
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164
Forks
30
Language
Verilog
License
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Last pushed
Dec 13, 2020
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