Sentence examples similar to neural network location from inspiring English sources

A neural network with an object location map as input was trained to construct a number-selective coding system at output.

This paper attempts to predict the Total Electron Content using adaptive recurrent Neural Network at three different locations of India.

He also developed a recurrent neural network model for predicting the location of the eye from initial onset of an eye movement, and he provided a theoretical account for why neural network activations and weights may be binarized with only nominal effects on performance, thus resulting in a dramatic reduction in compute time and power consumption.

The frequency shifts from these 10 test cases (at each noise level) were then input into three inverse algorithms, namely graphical technique (GT), surrogate-assisted optimization (SAO) and artificial neural network (ANN), to predict the location, size and interface of delaminations in a composite beam.

These are reviewed in this paper and we describe preliminary results of an Artificial Neural Network (ANN) model that predicts location specific hourly temperatures for London, taking into account radial distance from central London, hourly air temperature measured at the meteorological station and associated synoptic weather data.

The angle of incidence and the received power can be utilized (in theory) to train a neural network to identify the relative location of a user and grant access accordingly.

If less than three well-defined genotype clusters are observed, GenCall uses a neural network model to estimate the location and shape of the undefined clusters.

Shepherd et al. [ 9] used a neural network to predict both the location and types of β-turn in protein; they incorporated secondary structure information on the features used as input to the NN.

This module exploits a neural network algorithm to find the best location for placing the spheres within the atomic coordinates [33].

A neural network was employed for modeling the shockwave location through the nozzle using a better quality dataset.

The YOLOv2 convolutional neural network was trained to predict the spatial locations of people in each image frame of data using annotated bounding boxes of the spatial locations of people in 1379 frames of patient data.