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Industrial automation applications can benefit from the use of CogniMem technology to assist human effort where hard physical, monotonous, or dangerous requirements demand the augmented use of technology. The CogniMem neurons can be trained to recognize discrete objects, textures or patterns. Its non-linear classifier is ideal to cope with fuzzy or ill-defined problems such as food and surface inspection. Depending on the application, the recognition engines can be configured to identity and classify objects, but also to report novelty or anomalies.

  • Programmable Logic Controller – event detection or a sensor input like an image sensor can provide decision input via a simple serial RS485 or I2C interface to the controller for making adjustments or correcting a problem.
    Learn more about the V1KU Module...
  • Motion Control – Servo or actuator control. Set point control where elimination of overshoot or speed to achieve set point is crucial to the application.
    Learn more about the CM1K Chip...
  • Robotics - Video scanning for part selection, temperature, pressure other sensor input for sensor fusion and correlation to advanced process control. Command recognition.
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  • Machine Vision & Inspection – examples include date code detection and quality check of legibility. Defect detection on plain and/or textured surfaces in varying lighting conditions. Alignment of materials to be further processed.
    Learn more about the V1KU Module...
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car recognition, cognimem car identifier, vehicle recognition, cognimem vehicle recognition, CogniMem, Cognitive Computing, Artificial intelligence,clustering,data mining,expandable neural network,global sensing,Machine learning,neural network chip,neuron chip,neuronal processor,neurons,parallel neural network,pattern matching,pattern recognition chip,Restricted Coulomb Energy,smart sensors,super computing,trainable neural network
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