on-device-ml
There are 4 repositories under on-device-ml topic.
NexaAI / nexa-sdk
On device AI inference in minutes—now for MLX & GGUF and Qualcomm NPU, with Android and iOS coming soon.
Language:Go 4785xliucs / MTTS-CAN
Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement (NeurIPS 2020)
Language:Python 195sayakpaul / Adventures-in-TensorFlow-Lite
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
Language:Jupyter Notebook 174shubham0204 / Android-Document-QA
A custom RAG pipeline for multi-document QA from PDF/DOCX documents, in Android
Language:Kotlin 99ubicomplab / rppg-web
This is a web demo for camera-based PPG sensing (rPPG).
Language:TypeScript 85- Depth-Anything-Android
An Android app running inference on Depth-Anything and Depth-Anything-V2
Language:Kotlin 45 Embeddings from sentence-transformers in Android! Supports all-MiniLM-L6-V2, bge-small-en, snowflake-arctic, model2vec models and more
Language:Kotlin 40roboflow / inference-server-old
Object detection inference with Roboflow Train models on NVIDIA Jetson devices.
Language:JavaScript 14Nokia-Bell-Labs / data-channel-extension
[NeurIPS'24] DEX: Data Channel Extension for Efficient CNN Inference on Tiny AI Accelerators
Language:Jupyter Notebook 10denissimon / distributed-model-training
Approach to implementing distributed training of an ML model: server/device training for iOS.
Language:Swift 8hissain / AndroidSemanticSearch
A minimalistic Android app showcasing semantic search using ObjectBox and Lucene KNN, leveraging the MiniLM-L6-V2 embedding model and bert_vocab.txt for efficient retrieval.
Language:Jupyter Notebook 3sid-sr / FedSMS
End-to-end on-device federated learning, "An On-Device Federated Learning System for SMS Spam Classification", IEEE MIT URTC 2022
Language:JavaScript 3Abhiek187 / MiniBrainAge
An Android app where users draw a number and machine learning does the rest
Language:Kotlin 2luix / SponsorMe
SponsorMe is a project to help provide access to digital tools for learning, powered by on-device machine learning, innovation and willingness, to those people that have limited access to technology due to demographics, disabilities, economy or other multiple reasons.
Language:Kotlin 2andreapisa9 / bayesian-elm-search
As described in "Towards Full On-Tiny-Device Learning: Guided Search for a Randomly Initialized Neural Network"
Language:Python 1- Language:Jupyter Notebook 1
ivelin / fall-detection
Python ML library for person fall detection. Intended for IoT deployments with on-device inference and on-device transfer learning.
Language:Jupyter Notebook 1izakariyya / sim-virtual-fed-dnn
*Resource Efficient Federated Deep Learning for IoT Security Monitoring
Language:Python 1kyomangold / AI-GestureControl
Control your computer using hand gestures with AI, using Google's MediaPipe and OAK-D Lite camera.
Language:Python 1- Language:Java 1
karayanni / Distributed-KS-Test
A system for monitoring statistical data distribution shifts in distributed settings
Language:Jupyter Notebook 0sanketrout / -AndroidDevChallenge
#AndroidDevChallenge
0afondiel / Intro-to-On-Device-AI-Qualcomm
Notes and resources from Qualcomm On-device AI course, provided by DeepLearningAI
Language:Jupyter Notebookirvingvjuarez / rockedia-paper-pipe
Rock-Paper-Scissors game, using On-Device MachineLearning.
Language:TypeScripttheterminalguy / on-device-llm-demo
On-Device LLM demo with Google's MediaPipe
Language:JavaScript
