Recurrent neural networks (RNNs) have been widely used to model sequential neural
dynamics (“neural sequences”) of cortical circuits in cognitive and motor tasks. Efforts to …

Defining a multi-target motion model, an important step of tracking algorithms, is a
challenging task due to various factors, from its theoretical formulation to its computational …

This paper addresses the problem of fixed motion and measurement models for multi-target
filtering using an adaptive learning framework. This is performed by defining target tuples …

Filtering point targets in highly cluttered and noisy data frames can be very challenging,
especially for complex target motions. Fixed motion models can fail to provide accurate …

This thesis deals with recurrent neural networks, a particular class of artificial neural
networks which can learn a generative model of input sequences. The input is mapped …