Implementation of Edge Impulse's web classifier onto Android and iOS apps.
An AI/IOT smarthouse powered by Jetson Nano that only opens the door to Avengers action-figures with a voice welcome message
Pico Edge Impulse ML powered barrel that detects shots from a Nerf Blaster and simulates the barrel heating up with an LED.
Implementing the use of the MVTec AD database, the anomalib library, and the Patchcore model with the bottle class
Using GPT-2 models to generate text on a Raspberry Pi locally.
An exploration of accelerating the MediaPipe models with MemryX's MX3 AI Accelerator.
The Python implementation of the OFA-YOLO network from the Vitis AI 3.0 Model Zoo for real-time object detection
An extended tutorial on neural machine translation with attention mechanism algorithm.
A robotics mask detector that detects masks and indicate using leds.
Train a domain-specific image to keywords model that is 200x lighter (9MB) and runs with low latency on hardware such as Raspberry Pi 4.
This project compares inferencing MobileNet and EfficientNet-Lite on the MaaXBoard vs Coral dev board and Raspberry Pi.
Possible temperature monitoring and alert system for industries, preferably pharmacies.
TinyML based Door Lock detector using Edge Impulse Software which detects whether the door is not locked properly based on sound
You're not funny, but AI is! GigglyGram uses generative AI to turn you into a witty conversationalist with clever comebacks and memes.
AI is improving, we are becoming more dependent on it, and soon it will turn on us — unless we save ourselves with 1990s digital organizers.
With so many distractions surrounding young drivers it's easy to develop bad habits early on that lead to serious problems down the road.
Mount a camera in an industrial or manufacturing location to detect worker falls with computer vision.
How to use ESP-EYE to run image recognition to recognize hand gestures for rock, paper, and scissors, and how to train it on your own data.
A TinyML-powered CV cane to solve an everyday challenge for the blind - crossing the street.
A the list of four techniques, that can be helpful when aiming for running real-time model inference on Raspberry Pi 4. Ready? Let’s go!
Here, I will be implementing a machine learning model on a remote Raspberry Pi connected over a cellular module.
Monitoring river water quality based on open-design multi-parameter sonde, built along with QuickFeather and SensiML service.
Unleashing double the speed by harnessing dual-device parallelism for diffusion-driven video generation.
Poison ivy causes painful rashes & is found in places with poor reception (forests). Use this edge ML tool to ID poison ivy on your hike!
