Biologically Inspired Approaches toAutomated Feature Extraction and Target

Recognition

Speaker: Yi-Chun KeAdviser: Bo-Chi Lai

outline

• Introduction• Method• conclusion

Introduction

• computational models of biological vision and learning

• Vision models– long-range grouping– figure/ground segmentation

• memory models– bottom-up– top-down

Introduction

• cognitive and neural computations to technological applications– open-source code– user-friendly– integrated vision and recognition systems

• Recognition– Adaptive Resonance Theory (ART)• training

– winner-take-all coding

• testing– distributed coding

Method

• Vision– Boundary Contour System and Feature Contour

System (BCS/FCS)• long-range boundary completion• featural filling-in

conclusion

• ATR is colsing human cognitive information processing

• new information fusion methodologies are not limited to the image domain– medical data– improve marketing