Want to build your own TinyML image recognition application? This blog contains all the necessary details for you to get started
A tinyML vision model that can classify pictures of people based on whether they are wearing a mask or not.
Imagine a world where even the tiniest devices can 'see' and understand their surroundings.
Early detection of climate change by monitoring frogs
Learn how to build a tiny audio classification wearable that can identify dog sounds.The model is trained on synthetic data from ElevenLabs.
Why type the entire cheat code again and again when you can simply use gestures?
Answer to the embedded developer’s dilemma. AutoML introduced by Edge Impulse.
Most mask detection systems use camera modules but mine works on microphone data.
Recognize and detect words on Arduino Nano 33 Sense with trained datasets and Tensorflow lite
As the vision-based technology of Gastroscopic Image diagnostic recognition is an important part of AI Healthcare.
Let's get to know how "Hey Siri" or "Hey Google" work!
Use a Nicla Sense ME with an Edge Impulse model attached to the sleeve of a K-way jacket for gesture recognition and bad weather prediction.
Detect impacts in real-time using TinyML with the Arduino Nicla Vision, without modifying a single line of C++ code.
Extracting meaningful features from audio signals. How does Edge Impulse MFCC block work?
Revolutionizing Building Maintenance: Introducing GLEWBOT, the Bioinspired Climbing Robot for Flawless Wall Inspection
Automatic FOMO-based label inspection using computer vision and a web app.
This is a TinyML project based on TensorFlow Lite and Arduino Nano 33 Sense board. Under the instruction of 《TinyML》.
Enhance Arduino Nicla projects making them speak over WiFi.
A watcher device to monitor the room occupation
I wonder what our pets do during the day. Especially when we are not at home. We get information from video surveillance cameras on the Rasp
An embedded application that uses an 18KB model, trained on a dataset of speech commands, to classify spoken audio.
This TinyML solution recognizes screams and cries of workers who have been caught in an accident
This blog contains all the necessary info to optimize your TinyML applications
A smart cat feeder based on esp32s3
