Sentence examples for multiple neural networks from inspiring English sources

Given an input frame (left), the deep-learning model has multiple neural networks that each predict an action.

The experimental results demonstrate that the system predictability can be significantly improved by combing multiple neural networks.

The first is a single network approach whereas the second contains multiple neural networks in a hierarchy, termed a "mixture of experts" approach.

Evaluation of the performance of multiple neural networks is performed, using different levels of information, and optimization results are presented on a detailed house simulation model.

Our study includes multi-class pattern classification using either a system of multiple neural networks or a single neural network, and modeling pattern classes using one-against-all, one-against-one, one-against-higher-order, and P-against-Q.

In this work, control of a pH neutralization process is established by performing the following tasks: (i) development of three neural network models, (ii) tuning the multiple neural networks using a novel real coded genetic algorithm (RCGA), and (iii) design of a multi-model predictive controller (MPC).

To that end, we explore and study multiple neural network architectures, including novel NCC-networks, which are specifically adapted to this task.

Decades of research in this disorder have identified abnormalities in neurotransmitter systems, and there is a growing appreciation that signal transduction pathways play a crucial role in mediating the dysfunction in multiple neural network systems and physiological processes (Bhalla and Iyengar [2007]).

In models B and C, the multiple neural network structure was simulated by storing multiple weight vectors W(k) x and W(k) y which can be trained or retrieved when needed for any particular task k.

Each electrode is surrounded by multiple cells (Fig. 2a) and can record activity from either single or multiple established neural networks.

A New Supervised Learning Algorithm for Multiple Spiking Neural Networks -- 16.