A new classifier for movies has been developed by researchers at the University of San Antonio and the National Institute of Standards and Technology (NIST) in the United States.
They are hoping to use a technique called convolutional neural network (CNN) to classify movies, said the study’s lead author, professor Daniela Mazzone.
The CNN method has been used to create other classifiers including the popular classifier dubbed the CNNs “penguin algorithm”, which is based on deep learning.
CNNs have also been used for the classification of images.
The new CNN classifier, however, uses convolutionality.
CNN uses an algorithm to extract features from an image that are then applied to the image to create a set of classifications.
CNN convolution can be applied to image data to produce a classification.
CNN’s convolution is similar to what’s used in the CNN machine learning algorithm, which uses deep learning to classify images.
CNN has also been shown to be able to recognize patterns in images.
Mazzine explained that the CNN classifiers they created can learn from each other, and this can be used to train them.
They also can use other kinds of learning models.
“We hope to have this machine learning technology on the market in the next year,” Mazzie said.
The research was published online in the journal Nature Methods.
The study was supported by grants from the National Institutes of Health (NIH) and the U.S. Department of Energy.
It was also supported by a joint grant from the University at Buffalo and the Massachusetts Institute of Technology.