Creating a thermal imaging overlay for the PYNQ Z2.
Safe Meeting keeps an eye on you during your video conferences, and if it sees your underwear, the video is immediately muted.
Use OpenCV and Tesseract on MaaXBoard to find letters in magazine pages for your ransom note.
Vectron AI interfaces with the Vectron 64 computer (6502 CPU @ 1MHz, 32KB RAM, 32KB ROM) to provide gesture detecting AI.
Get machine learning running on your MaaXBoard using TensorFlow
Detect any thing at any time using a Camera Serial Interface Infrared Camera on an NVIDIA Jetson Nano with Azure IoT and Cognitive Services.
Get machine vision running on your MaaXBoard using OpenCV.
Deep Clean watches a room and flags all surfaces as they are touched for special attention on the next cleaning to prevent disease spread.
Hardware platform combined with DeepLib, an easy to use but yet powerful DeepStream based Python Library, and a web IDE
Use a webcam and a Raspberry Pi 4 to extract information from QR codes and even make your own with Python
We experiment with visual anomaly detection to develop techniques for reducing bandwidth consumption in streaming IoT applications.
This computer vision booth analyzes users throwing darts from multiple cameras, scoring each dart before logging data to the cloud.
breakthrough. automated. [kannon]. instrument.
The M5Stick-V is an AIOT (AI + IOT) camera with machine vision capabilities.
Using the TensorFlow Lite library, we can flash tiny machine learning models on an Arduino to detect humans from a camera.
Connect Nvidia Jetson devices to Azure IoT Central with IoT Plug and Play to command and control DeepStream workloads in a custom dashboard!
Texas Instruments Deep Learning API and examples ported onto BeagleBone AI's default Debian distribution image and mjpg-streamer filters.
The title says it all! This project uses OpenCV and a convolutional neural network in PYNQ on an Ultra96 V2 to create a smart lock.
Forget recycling, this robot does it for you!
I was looking for a way to show students how computer vision object classification and detection worked then I reached for another M&M...
This article is a "tips and tricks" for running Azure IoT Edge on Raspberry Pi. Plus Raspberry Pi 4 Tips for cooling, USB 3, and Docker.
Using Azure IoT Edge on Nvidia Jetson Nano with Time Series Insights to detect objects in video feeds with offsite recording to the cloud.
PYNQ is great for accelerating Python applications in programmable logic. Let's take a look at how we can use it with OpenMV camera.
To develop an Android application for object detection which is supported by Snapdragon mobile platforms with neural processing SDK.