Performance analysis on visual attention using spiking and oscillatory neural model
by A. Diana Andrushia; R. Thangarajan; Greeshma Sebastian
International Journal of Computational Vision and Robotics (IJCVR), Vol. 3, No. 4, 2013

Abstract: Visual attention is a process of sustained concentration on a specific stimulus. This concentration can be increased by activating the nucleus basalis in the basal forebrain using the spiking neuron model. Input stimulus is converted into spikes. Neurons are transmitting information in the form of pulse. By using this information spiking neuron model for the basal forebrain is simulated. Bottom-up and top-down method is used in lateral geniculate nucleus (LGN). The feedback connections are applied in the visual cortex for the enhancement of visual attention. To analyse the performance of spiking and oscillatory model segmentation and separation accuracy are obtained which shows the oscillatory model produce better accuracy for visual stimuli.

Online publication date: Fri, 18-Jul-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Vision and Robotics (IJCVR):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com