The highest quality sound in a small. lightweight package.
You've collected your data to train your model. Now what? I break down the annotation tools CVAT vs VoTT.
IoT-JumpWay-Intel-Examples - Examples of using the IoT JumpWay with the Intel® IoT Developer Kit, Intel® Edison board, Intel® Galileo, In...
A smartphone arm was created using myCobot and the OAK-D OpenCV DepthAI camera, allowing users to always enjoy videos right in front of them
A rubber band shooter that sits on top of a pan-tilt stage with computer vision abilities.
Connecting to the master computer vision system for object recognition for low processing costs.
Machine learning at the edge for distress calls surveys using drones.
A low-cost vision-based anti-sleep alarm system that detects driver drowsiness using OpenCV and alerts via Arduino-controlled buzzer and LED
I have purchased each of the Compute Modules but never build or tested them, this time I would get the dual cameras working and then... ?
bAIwatch gets images from a public webcam from a beach, evaluates the surfing conditions and warns me it the waves are good enough.
integration of Amazon Echo in intel edison board
Detects and alerts authorities about human entry into restricted areas such as wildlife sanctuaries, protected forests, or sensitive zones.
Revolutionize playtime with my Raspberry Pi-powered Ball Tracking Robot. Explore the future of interactive robotics in this DIY project
A robot arm that detects kids and throws candy at them.
An autonomous vehicle on a BBAI-64 that's capable of lane-keeping and stopping at a stop box (good for getaways).
A compact robotic arm pre-loaded with LLM & Computer Vision technical cases that can quickly get you started and master AI skills.
This blog contains all the necessary info to optimize your TinyML applications
UAV tracking and identification of endangered wildlife
How to use YOLOv8 to train a classification model using a custom dataset on Seeed Studio reComputer J4012
Stereo Depth Perception on ESP32 S3, completely on board.
A compact ESP32 edge-AI and AR module powering a rover with audio, vision, and offline ML for hands-on robotics projects.
Build a machine learning model using a federated training framework to keep data on-device, train locally, and update a global model.
This device is a conveyor, at the input of which raw grain enters, and at the output we get grain clean from dirt.
Multi-stage inference with Edge Impulse/Tensorflow Lite - Raspberry Pi 4 Compute Module
