/challenges-projects/design-challenges/eye-on-intelligence-challenge/b/blog/posts/blog-5---fruitvision-scale---exploring-deep-learning-applications-with-amd-zynq-7000Introduction In this blog post, I&#39;ll explore Deep Learning and quantization using the AMD Zynq 7000. I&#39;m focusing on how these techniques can be applied to Computer Vision for my FruitVision Scale project. To do this, I&#39;ll use the Zynq 7000 and PYNQ.en-USTelligent Community 12https://community.element14.com/challenges-projects/design-challenges/eye-on-intelligence-challenge/b/blog/posts/blog-5---fruitvision-scale---exploring-deep-learning-applications-with-amd-zynq-7000Wed, 12 Feb 2025 11:15:40 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:4514f159-726e-47e8-80fd-c4c232c8bdd7Sharizal1<p>Thank you and thumbs up for the great knowledge sharing. I am planning to develop deep learning project with my students using similar Zynq 7000 SOC.</p> <p>For the Digilent Arty Z7-10, is&nbsp;this model can work similar to your demo using the Z7-20?</p> <p>Also, you mentioned the PYNQ-Z1. Do we need to have this component interface with the Arty Z7-20? Or optional? I could not really understand this part as you exhibit only the photos with Arty Z7-20 without the PYNQ-Z1 board. Correct me if I am wrong.</p> <p>Thank you for your guidance and help.</p> <p></p><img src="https://community.element14.com/aggbug?PostID=28490&AppID=445&AppType=Weblog&ContentType=0" width="1" height="1">