We present a new approach to integrated motion estimation and segmentation by combining methods from discrete and continuous optimization. The velocity of each of a set of regions ...
This paper presents our Recurrent Control Neural Network (RCNN), which is a model-based approach for a data-efficient modelling and control of reinforcement learning problems in di...
The complexity of gene regulatory network models stems from the fact that the models should be able to represent continuous, discrete as well as stochastic aspects of gene regulati...
To support more efficient video database management, this paper explores the concept of video association mining, with which the association patterns are characterized by sequenti...
Abstract-- We address a new problem--the invertibility problem for continuous-time switched linear systems, which is the problem of recovering the switching signal and the input un...