The Expansion Module

NT Adaptive ™ Raspberry Pi

Adaptive neural network expansion module ready to plug into your Raspberry Pi single board computer so you can access a NeuroMem® digital neural network of 576 neurons to learn, classify and monitor your data. Supports both UART or USB interface. This module can be interface to other microcontroller board with a USB C connector.

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    NT Adaptive Module with 576 neurons designed for demonstration, training, developing of neuromorphic chips capabilities. The module is easily connected to the Rasperry Pi and other computers via micro USB.

    Video Examples

    The opportunity of neuromorphic to identify the positions of circuit breakers, LEDs indicating real equipment is presented.

    The program is developed on Python and combines various options for demonstrating the possibility of neuromorphic chips. Recognition of positions of automatic power supply units, light indication of control lamps, indications of dial gauges, values of seven-segment indicators, positions of biscuit switches.

    The demo program written in Python is shown. This demo program uses a combination of the OpenCV open library and the CM1K chip (NM500) when working with the PCIe expansion board. OpenCV was used to search for faces in photographs, the training and recognition of the faces themselves was performed using neuromorphic chips.

    Demonstration of the program developed on Python. Demonstration of the sequence of image selection, ROI selection, selection and tuning of parameters of a neuromorphic chip, such as MAXIF, categories, training and verification of learning outcomes. This program uses neuromorphic chips on a PCIe board.

    NT Adaptive Raspberry PI Artificial Intelligence Module designed for various signals identification. Module can recognize static images, sounds, various electrical signals, texts, data. Hardware level neuromorphic recognition process will accelerate any computer AI possibilities. Module recognize signals in microseconds with only milliwats of power.


    • Identification;
    • Classification;
    • Novelty detection;
    • Anomaly detection;
    • Image contextual segmentation;
    • Edge detection;
    • Noise removal;
    • Image compression;

    and others.

    Areas of implementation:

    • Hobby;
    • Education;
    • Studies;
    • Industry;
    • Agriculture;
    • Medicine;
    • Security;
    • Statistics;

    and others.

    NT Adaptive Raspberry PI module dimensions: 52x20x10 mm

    Module can be connected via Micro USB or TTL pins.

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