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CogniMem News

CogniMem releases Volume 1, Issue 3 of the CogniMem Communique'.

Read the Newsletter


GlobalSensing launches NeuroPic and NeuroFPGA products based on the Cognimem CM1K



CogniMem announces joining the Embedded Vision Alliance to advance the use of vision in embedded applications.



CogniMem announces 2 new opportunities to learn cognitive computing, Online & Classroom Training.


CogniMem announces new CM1K prototyping module for ease of board development: CM1K-PGA69



See article describing superiority of CogniMem hardware based RBF classifier in performance and accuracy over S/W alone based approaches for Face Recognition!

“A Hardware/Software Co-design Model for Face Recognition using Cognimem Neural Network chip”
By Santu Sardar, Gaurav Tewari, K.A. Babu DRDO; Hyderabad, India



“Target Tracking with the Zero Instruction Set Computer”
Evaluation of the Computational Capacity of the ZISC in Target Tracking By Wendall C. Deck




CogniMem Technologies Inc.

Massively Parallel Hardware Acceleration for Pattern Recognition

When pattern recognition is the problem – CogniMem’s Cognitive Computing chips are the answer. CogniMem is leading the industry with Cognitive Sensing & Computing - going beyond Von Neumann computer architecture to deliver unmatched levels of processing at far less energy.


Intelligence for Sensing

CogniMem enables trainable adaptive filtering for vision, speech and other sensing devices while reducing cost and energy.


Intelligence for Data Mining

CogniMem enables a flexible and scalable architecture natively implementing well-known non-linear classifiers Radial Basis Functions and K-Nearest Neighbor. Latency of the recognition stays fixed independent of the amount of memories being searched at very low power.


  • Trainable: automatic model generator
  • Reliable: re-known pattern classifier
  • Ease of Use: software tools and SDK
  • High Speed: board and chipsets
  • Low Power: board and chipsets
  • Object Recognition
  • Target Tracking
  • Signal Classification
  • Data Classification, Clustering
  • Anomaly / Novelty Detection
  • Template Matching

 

CogniMem for "Cognitive Memory"