Topic: on-device-ai Goto Github
Some thing interesting about on-device-ai
Some thing interesting about on-device-ai
on-device-ai,Firebase MLkit vision demo app
User: azzeddinech
on-device-ai,AubAI brings you on-device gen-AI capabilities, including offline text generation and more, directly within your app.
User: brutalcoding
Home Page: https://pub.dev/packages/aub_ai
on-device-ai,Official PyTorch implementation of "EdgeSAM: Prompt-In-the-Loop Distillation for On-Device Deployment of SAM"
User: chongzhou96
Home Page: https://mmlab-ntu.com/project/edgesam/
on-device-ai,A Google Photos alternative, where your pictures never leave your phone! Classification happens on-device, leveraging pre-trained models. Available for Android and iOS.
User: cryptoboid
on-device-ai,2022 D.Com 동아리 대항전 Team "AEye" - Android Native App 개발을 위한 Repo.
Organization: dcom-khu
on-device-ai,Android Voice Activity Detection (VAD) library. Supports WebRTC VAD GMM, Silero VAD DNN, Yamnet VAD DNN models.
User: gkonovalov
on-device-ai,A python framework for designing high-performance Computer Vision pipelines at the Edge. Supports Coral Edge TPU, Raspberry Pi Camera, and more.
User: hav4ik
on-device-ai,Source code for my blog post series "On-device training with Core ML"
User: hollance
on-device-ai,A ready-to-use, minimal app that converts any speech into text.
User: hugo-dz
on-device-ai,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.
User: luix
on-device-ai,Double Quantization Experiment: Quantizing a Quantized model for On-device Deployment
User: mattjesc
on-device-ai,BLOCKSET: Efficient out of core tree ensemble inference
User: megh1241
on-device-ai,[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices
Organization: mit-han-lab
Home Page: https://arxiv.org/abs/1802.03494
on-device-ai,[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices
Organization: mit-han-lab
Home Page: https://arxiv.org/abs/1802.03494
on-device-ai,Binary Neural Network on IceStick FPGA.
Organization: mit-han-lab
on-device-ai,[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
Organization: mit-han-lab
Home Page: https://hanlab.mit.edu/projects/proxylessNAS/
on-device-ai,TinyChatEngine: On-Device LLM Inference Library
Organization: mit-han-lab
Home Page: https://mit-han-lab.github.io/TinyChatEngine/
on-device-ai,Simplified AI runtime integration for mobile app development
Organization: neuralize-ai
Home Page: https://runlocal.ai
on-device-ai,Kotlin bindings for Edgerunner
Organization: neuralize-ai
Home Page: https://github.com/neuralize-ai/edgerunner
on-device-ai,Recipes for on-device voice AI and local LLM
Organization: picovoice
Home Page: https://picovoice.ai/
on-device-ai,Object detection inference with Roboflow Train models on NVIDIA Jetson devices.
Organization: roboflow
Home Page: https://docs.roboflow.com/inference/nvidia-jetson
on-device-ai,On-device Neural Engine
Organization: samsung
on-device-ai,This is a web demo for camera-based PPG sensing (rPPG).
Organization: ubicomplab
Home Page: https://vitals.cs.washington.edu/
on-device-ai,Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement (NeurIPS 2020)
User: xliucs
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