Active learning aims to reduce the amount of labels required for classification. The main difficulty is to find a good trade-off between exploration and exploitation of the lab...
Sparse representation has been applied to visual tracking by finding the best candidate with minimal reconstruction error using target templates. However most sparse representati...
Standard Gene Expression Programming(GEP) works with fixed rate of mutation and crossover, ignoring the variation of the individual fitness, hence it works in the local optimum st...
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
Distributed mobile applications operate on devices with diverse capabilities, in heterogeneous environments, where parameters such as processor, memory and network utilisation, are...