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Biological Neural Processing as a Paradigm for Visual Pattern Recognition 

A bat, with a brain that is the size of a plum, maneuvers extremely well, even when compared to our best air traffic control systems.  This kind of performance is far from anomalous.  In fact, most biological systems perform as well, if not better, than our best computers.  This applies to many cognitive functions, including image pattern recognition.

While we are limited in what we can cover in this short time, we will discuss some of the biological systems and how they operate.  Comparisons will be made to our current state of the art computer algorithms and systems.  These biological neural processors are amazing in their simplicity and ability to recognize patterns and images.

About the Speaker

Dr Morantz, a senior member of the IEEE and member of the Computer and the Computational Intelligence Societies, researches methods to improve our decision making.  His most recent work is in intelligent classification utilizing machine cognition.  The goal is to understand how pattern recognition and cognitive function are accomplished in the biological world and then to be able to implement this in the machine environment in order to improve the quality of our decision making. 

Dr Morantz has his BS in CIS/EE, his MS and PhD in Mathematical Decision Science with a minor in computer science and an emphasis in artificial intelligence.  He has taken additional courses in Computational BioScience and the sciences in general.  He also has over 150 hours from Raytheon Learning Institute as well as numerous other continuing education courses.

Dr Morantz has given many presentations on advanced methodologies around the country and is currently on the editorial board of the International Journal of Data Mining, Modeling, and Management.  He also has many publications in this area as well.    


20091202BiologicalProcessing.pdf (Presentation PDF)