Aplicaciones de clasificación y segmentación de imágenes

Generate Code for a Deep Learning Network for x86-64 Platforms Using Advanced Vector Instructions

Generate code for deep learning networks, targeting an Intel^® processor.

Generate Code and Deploy SqueezeNet Network to Raspberry Pi

Code generation with ARM^® Compute Library when you do not have a hardware support package.

Deep Learning Prediction with ARM Compute Using codegen

Generate code for deep learning networks, targeting an ARM processor.

Generate Code and Deploy MobileNet-v2 Network to Raspberry Pi

Use the MobileNet-V2 network for object prediction on external hardware.

Code Generation for Semantic Segmentation Application on ARM Neon Targets That Uses U-Net

Generate a static library that performs image segmentation by using the deep learning network U-Net on ARM targets.

Generate Code for TensorFlow Lite (TFLite) Model and Deploy on Raspberry Pi

Generate code that uses a TensorFlow™ Lite model for inference.

Deploy Classification Application Using Mobilenet-V3 TensorFlow Lite Model on Host and Raspberry Pi

Generate code for a classification segmentation application that uses TensorFlow Lite model.

Deploy Semantic Segmentation Application Using TensorFlow Lite Model on Host and Raspberry Pi

Generate code for an image segmentation application that uses TensorFlow Lite model.

Deploy Pose Estimation Application Using TensorFlow Lite Model (TFLite) Model on Host and Raspberry Pi