In this paper we present a novel scale invariant interest point detector of blobs which incorporates the idea of blob movement along the scales. This trajectory of the blobs throug...
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Recent research has shown that the provisional count of votes of an ensemble of classifiers can be used to estimate the probability that the final ensemble prediction coincides w...
This paper proposes a spiking neural network (SNN) of the mammalian auditory midbrain to achieve binaural multiple sound source localisation. The network is inspired by neurophysio...
Jindong Liu, David Perez-Gonzalez, Adrian Rees, Ha...
Electronic photography is gaining parts of the photography market and tends to replace gradually all argentic photography. The combination of digital camera and computer technolog...