Object detection inference with Roboflow Train models on NVIDIA Jetson devices.

HARNet: Towards On-Device Incremental Learning using Deep Ensembles on Constrained Devices for Human Activity Recognition

This repository contains the spreadsheet of the quantitative analysis performed for the paper "Suitability of Forward-Forward and PEPITA Learning to MLCommons-Tiny benchmarks".

This repository contains the code to create on-device machine learning models for species classification.

This project is simple training tensorflowlite on mobile device - android for braintumor classification

Python ML library for person fall detection. Intended for IoT deployments with on-device inference and on-device transfer learning.

A comprehensive set of notes and resources for a crash course on deploying AI models on edge devices, provided by DeepLearningAI and taught by Krishna Sridhar from Qualcomm.

Predict Gender in real time by showing your hand in your camera.

Custom core models with updatable layers for on device learning