A system and method facilitating pattern recognition is provided. The invention includes a pattern recognition system having a convolutional neural network employing feature extraction layer(s) and classifier layer(s). The feature extraction layer(s) comprises convolutional layers and the classifier layer(s) comprises fully connected layers. The pattern recognition system can be trained utilizing a calculated cross entropy error. The calculated cross entropy error is utilized to update trainable parameters of the pattern recognition system.

 
Web www.patentalert.com

< Methods for dynamically accessing, processing, and presenting data acquired from disparate data sources

< Interface between programming languages and method therefor

> Model-free adaptive control of quality variables

> Performance assessment of data classifiers

~ 00246