You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
Biological understandings have served as the basis for new computational approaches. A prime example is artificial
neural nets which are based on the biological understanding of the trainability of neural synapses. In this paper, we will
investigate features of the biological vision system to see if they can also be exploited. These features are 1) the
neuron’s refractory period - the period of time after the neuron fires before it can fire again and 2) the ocular
microtremor which moves the retinal neural array relative to the image. The short term memory due to the refractory
period allows the before and after movement views to be compared. This paper will discuss the investigation of the
implications of these two features.
The alert did not successfully save. Please try again later.
Thomas C. Fall, "Refractory neural nets and vision," Proc. SPIE 9019, Image Processing: Algorithms and Systems XII, 90190H (25 February 2014); https://doi.org/10.1117/12.2040212