Abstract. This paper examines the generalization capability in learning multiple temporal patterns by the recurrent neural network with parametric bias (RNNPB). Our simulation expe...
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
In this paper we present a generative model and learning procedure for unsupervised video clustering into scenes. The work addresses two important problems: realistic modeling of ...
Nemanja Petrovic, Aleksandar Ivanovic, Nebojsa Joj...
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
In this paper we present a unsupervised learning based approach for sub-pixel motion estimation. The novelty of this work is the learning based method itself which tries to learn ...
Mithun Das Gupta, Nemanja Petrovic, ShyamSundar Ra...