Access to eBooks is limited to institutions that have purchased or currently subscribe to the SPIE eBooks program. eBooks are not available via an individual subscription. SPIE books (print and digital) may be purchased individually on SPIE.Org.

Contact your librarian to recommend SPIE eBooks for your organization.
Chapter 4:
Data Collection, Preparation, Labeling, and Input Coding
Since neural networks are data driven, the adage "garbage in, garbage out"€ is highly relevant to the task of building a neural network. Proper collection, preparation, labeling, and coding of the data can make the difference between a successful and unsuccessful experience with neural networks. While the process of collecting data seems simple, the network designer should put some thought into the data-collection process. The designer needs to decide what he wants the neural network to do and what data requirements are needed to train the network. Will it be a classifier, an estimator (modeler), or a self-organizer (clusterer)? The designer needs to determine how and from where to obtain the data and what types of data to collect. He must also determine what the neural network will output in response to the data used as the network input. The steps in a typical data-collection plan are described next.
Online access to SPIE eBooks is limited to subscribing institutions.

Back to Top