Learn how to deploy the best object detection algorithm to Jetson Nano and start building powerful edge computing applications.
This project is an example of how AI can be used for counting objects in a quick and efficient way using embedded Machine Learning.
Learn how to easily set up machine learning inference capabilities on the AMD/Xilinx KV260 Vision AI starter kit running Ubuntu desktop
Sensitive Pulse Induction metal detector which is based on ARM STM32 microcontroller. It can detect metal coih at distance of 30cm.
This tutorial is on "How to install Petalinux 2021.1, Building Petalinux BSP Project of Kria KV260 with SmartCam & run FaceDetection App"!
Computer Vision Exploration with the help of Edge Impulse and Arduino.
Exploring Computer Vision applications such as Image Classification, Object Detection, and Pose estimation.
Get started using a Pi 3 with Intel's Neural Compute Stick 2, to detect objects and faces.
It's a robot cat toy that starts when motion detection and object recognition confirm a cat is present. It also has a camera & web app.
Use an antenna and SDR to get satellite imagery data from NASA satellites, then run object detection on the images to identify rain clouds!
Deploying YOLOv8 on Raspberry Pi Zero 2W for Real-Time Bee Counting at the Hive Entrance.
Dual AI Camera using Grove Vision AI V2 and Xiao ESP32S3 Sense to detect and capture images of hummingbirds.
Self checkout smart cashier using object detection to calculate number of items and total price for your purchase.
Monitor road usage with this camera-equipped device, which detects and logs vehicle traffic to a cloud database.
Discover how to set up and run YOLOv12 on Jetson Nano 4GB for real-time object detection. Efficient, powerful AI at the edge!
Using the KV260 DPU Core & ML to Detect Birds in the Vicinity of Airport and Preventing Birds Strikes During Approach/ Landing / Take-off.
The role of the new SeeedStudio Grove Vision AI Module V2 in Wildlife Surveillance A review...
This robot will follow you where ever you go, just make sure to be in touch with it.
Deploying and inferencing a TFLite model trained using Edge Impulse Studio on M5Stack UnitV2
Learn how to deploy NVIDIA TAO Object Detection ML models on the NXP i. MX 93's dual-core Arm Cortex-A55 CPU and Ethos-U65 NPU.
This project is to showcase object detection using OAK-D, which is trained in SSD-MobileNet-V2 model with custom dataset.
Using YOLO on an Nvidia Jetson Nano to detect faces and objects in photos, videos, and live camera stream.
Computer Vision Exploration with the help of OpenMV, Edge Impulse, and Arduino.
Jetson car able to find objects, controlled through remote voice control using an Android Application which supports words in two languages.
