Inspired by gamma-band oscillations and other neurobiological discoveries, neural networks research shifts the emphasis towards temporal coding, which uses explicit times at which spikes occur as an essential dimension in neural representations. We present a feature linking model (FLM) that uses the timing of spikes to encode information. The first spiking time of FLM is applied to image enhancement, and the processing mechanisms are consistent with human visual system.
If you use the Feature linking model, we appreciate it if you cite the following paper:
@Article{zhan2016feature,
author = {Zhan, K. and Teng, J. and Shi, J. and Li, Q. and Wang, M.},
title = {Feature-linking model for image enhancement},
journal = {Neural Computation},
year = {2016},
volume = {28},
number = {6},
pages = {1072--1100},
publisher = {MIT Press}
}
If you have any questions, Feel free to contact me. (Email: ice.echo#gmail.com)
http://www.escience.cn/people/kzhan
