John Charles Newell

20200005150, Jan 2, 2020

Jun 29, 2018

16/023823

- Armonk NY, US
Stephen C. Hammer - Marietta GA, US
Micah Forster - Austin TX, US
John C. Newell - Austin TX, US

G06N 3/08
G06K 9/62
G06K 9/00
A63B 71/06
G06T 7/20

Using a simple cue to reduce a number of sequential frames included in a video that needs to be analyzed by an artificial neural network to predict information corresponding to a projectile depicted within the video is provided. A timing of the simple cue associated with the video is detected. The number of sequential frames within the video is reduced down to only those frames that are within a specified range of the simple cue. The artificial neural network is used to analyze the reduced number of sequential frames. The information corresponding to the projectile is predicted based on analyzing the reduced number of sequential frames using the artificial neural network.

20190294985, Sep 26, 2019

Mar 23, 2018

15/933918

- Armonk NY, US
Stephen C. HAMMER - Marietta GA, US
Joseph S. MABRY - Fulton GA, US
John C. NEWELL - Austin TX, US

G06N 5/04
G06N 3/08
G06F 15/18
G06F 17/30

Devices and methods for modeling streaming data are disclosed. A method includes: receiving, by a computing device, a local graph model; determining, by the computing device, a subgraph in the local graph model; acquiring, by the computing device, an external graph model; determining, by the computing device, a plurality of alternative subgraphs in the external graph model; determining, by the computing device, a score for each of the plurality of alternative subgraphs; selecting, by the computing device, an alternative subgraph having a highest score among the plurality of alternative subgraphs; and ensembling, by the computing device, the local graph model and the alternative subgraph having the highest score.

20180336459, Nov 22, 2018

May 22, 2017

15/601647

- Armonk NY, US
Stephen C. HAMMER - Marietta GA, US
John C. NEWELL - Austin TX, US
Craig M. TRIM - Sylmar CA, US

G06N 3/08
G06N 3/04
G06F 17/27

Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: running a comment examining process for processing comments of one or more user to provide a comment processing output; applying data of a dataset as training data for training a neural network to define a trained neural network, wherein the training data includes input node training data and output node training data; and generating a decision rule for the dataset based on a transfer function of the trained neural network, wherein the decision rule is based on the comment processing output.