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Recognizing complex patterns

Nature Neuroscience volume 5, pages 1093–1097 (2002)Cite this article

Abstract

How the brain recognizes complex patterns in the environment is a central, but little understood question in neuroscience. The problem is of great significance for a host of applications such as biometric-based access control, autonomous robots and content-based information management. Although some headway in these directions has been made, the current artificial systems do not match the robustness and versatility of their biological counterparts. Here I examine recognition tasks drawn from two different sensory modalities—face recognition and speaker/speech recognition. The goal is to characterize the present state of artificial recognition technologies for these tasks, the influence of neuroscience on the design of these systems and the key challenges they face.

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Figure 1: An example that highlights the challenge inherent in the face recognition task.
Figure 2: Four facial composites generated by an IdentiKit operator at the author's request.
Figure 3: Unlike current machine-based systems, human observers are able to handle significant degradations in face images.
Figure 4: At first glance, the image shown above seems to depict an ordinary shot of the current US president and vice-president.
Figure 5: Compensating for image degradations in a top-down manner.

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Acknowledgements

For a broad ranging review such as this, one has to draw upon the expertise of several colleagues. I am grateful for generous help from Keith Kluender, Steve Greenberg, Hynek Hermansky and Paul Griffin.

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  1. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, 02139, Massachusetts, USA

    Pawan Sinha

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  1. Pawan Sinha
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Sinha, P. Recognizing complex patterns. Nat Neurosci 5 (Suppl 11), 1093–1097 (2002). https://doi.org/10.1038/nn949

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