There are 2 repositories under on-device-ml topic.
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
This is a web demo for camera-based PPG sensing (rPPG).
A custom RAG pipeline for multi-document QA from PDF/DOCX documents, in Android
An Android app running inference on Depth-Anything and Depth-Anything-V2
Embeddings from sentence-transformers in Android! Supports all-MiniLM-L6-V2, bge-small-en, snowflake-arctic models and more
Object detection inference with Roboflow Train models on NVIDIA Jetson devices.
Approach to implementing distributed training of an ML model: server/device training for iOS.
An Android app where users draw a number and machine learning does the rest
Python ML library for person fall detection. Intended for IoT deployments with on-device inference and on-device transfer learning.
*Resource Efficient Federated Deep Learning for IoT Security Monitoring
Control your computer using hand gestures with AI, using Google's MediaPipe and OAK-D Lite camera.
As described in "Towards Full On-Tiny-Device Learning: Guided Search for a Randomly Initialized Neural Network"
A system for monitoring statistical data distribution shifts in distributed settings
#AndroidDevChallenge
Rock-Paper-Scissors game, using On-Device MachineLearning.