— Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional ...
Evolutionary multi-objective optimization of spiking neural networks for solving classification problems is studied in this paper. By means of a Paretobased multi-objective geneti...
The research work is carried out to enhance the recognition accuracy of neural network with Phase Only Correlation (POC) and reduce the time required for POC by refining its input...
This paper presents a neural network approach with successful implementation for the robot task-sequencing problem. The problem addresses the sequencing of tasks comprising loadin...
In this paper, we describe an adaptive approach to gesture for musical applications. Neural Network abstractions and interfaces are implemented in the Pure Data environment which ...