Spiking Neural Networks (SNNs) model the biological functions of the human brain enabling neuro/computer scientists to investigate how arrays of neurons can be used to solve comput...
Brendan P. Glackin, Jim Harkin, T. Martin McGinnit...
This paper focuses on a scheme for automated tumor recognition using images acquired during endoscopic sessions. The proposed recognition system is based on multi-layer feed forwa...
S. A. Karkanis, Dimitrios K. Iakovidis, Dimitrios ...
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
A scalable architecture to facilitate emergent (self-organized) task decomposition using neural networks and evolutionary algorithms is presented. Various control system architectu...
Jekanthan Thangavelautham, Gabriele M. T. D'Eleute...
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...