{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Programming Tech Brief By HackerNoon","title":"Deploying MobileNetV3 on NXP i.MX8MP: A Complete Edge AI Workflow for Handwritten Digit Recognition","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/ee00ea1b\"></iframe>","width":"100%","height":180,"duration":498,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/deploying-mobilenetv3-on-nxp-imx8mp-a-complete-edge-ai-workflow-for-handwritten-digit-recognition.\nThis article details how to port and run the MobileNetV3 model on the NXP i.MX8MP platform to achieve the function of handwritten digit recognition.\nCheck more stories related to programming at: https://hackernoon.com/c/programming.\n            You can also check exclusive content about #linux, #embedded-systems, #eiq, #mobilenetv3, #eiq-portal, #deep-learning-deployment, #model-training, #industrial-ai,  and more.\nThis story was written by: @hacker55465321. Learn more about this writer by checking @hacker55465321's about page,\n            and for more stories, please visit hackernoon.com.\nThis article details how to port and run the MobileNetV3 model on the NXP i.MX8MP platform to achieve the function of handwritten digit recognition. From dataset import, model training and validation to TensorFlow Lite quantization and deployment, it fully demonstrates the usage process of eIQ Portal tool.","thumbnail_url":"https://img.transistorcdn.com/KhCapPSRkLGL2Xw8888yuChkNRWthaKapLYTvNdu4W4/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMTY2LzE2ODM1/ODIzMzAtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}