Robotics Researcher and Student, Technical Writer
Using either the TFJS Task API or the TFLITE Web API you can now deploy Tensorflow Lite models on the web without even needing to convert them into Tensorflow.js format.
The TensorFlow Lite Model Maker library is a high-level library that simplifies the process of training a TensorFlow Lite model using a custom dataset. It uses transfer learning to reduce the amount of training data required and shorten the training time.
D2Go is a production-ready software system from FacebookResearch, which supports end-to-end model training and deployment for mobile platforms.
TensorFlow.js is a deep learning library providing you with the power to train and deploy your favorite deep learning models in the browser and Node.js.
With the recently released official Tensorflow 2 support for the Tensorflow Object Detection API, it's now possible to train your own custom object detection models with Tensorflow 2.
Learn how to use the Tensorflow Object Detection API with Tensorflow 2
The Arduino Nano 33 BLE Sense is an evolution of the traditional Arduino Nano, but featuring a lot more powerful processor, the nRF52840 from Nordic Semiconductors, a 32-bit ARM® Cortex™-M4 CPU running at 64 MHz.
Use TensorRT to run PyTorch models on the Jetson Nano.
Run Tensorflow model on the Jetson Nano by converting them into TensorRT format.
YOLO Object Detection on the Jetson Nano using TensorRT
Gilbert Tanner is a Robotics, Systems and Control student at ETH Zürich.
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