Yang Chen

US Patent:

59636530, Oct 5, 1999

Filed:

Jun 19, 1997

Appl. No.:

8/878863

Inventors:

Charles McNary - Los Angeles CA
Kurt Reiser - Los Angeles CA
David M. Doria - Los Angeles CA
David W. Webster - Los Angeles CA
Yang Chen - Los Angeles CA

Assignee:

Raytheon Company - Lexington MA

International Classification:

G06K 900
G06K 962
G01S 1300
G01S 1358

US Classification:

382103

Abstract:

A hierarchical object recognition method for aggregation, interpretation and classification of information from multiple sensor sources on the detection feature attribute level. The system extracts information derived from each sensor source to obtain detections and their feature attributes. At least two processing streams, one for each sensor source, are provided for converting the detections and their feature attributes into hypotheses on identity and class of detected objects. The detections are shared and combined between the two processing streams using hierarchical information fusion algorithms to determine which ones of the hypotheses on identity and class of detected objects have sufficient probabilities for classifying the information.

US Patent:

61157023, Sep 5, 2000

Filed:

Dec 23, 1997

Appl. No.:

8/998402

Inventors:

Kurt Reiser - Torrance CA
Yang Chen - Westlake Village CA

Assignee:

Hughes Electronics Corporation

International Classification:

G06F 1500

US Classification:

706 62

Abstract:

The present invention provides a method of performing statistical classification that can resolve conflict in independent sources of information, thereby creating a robust statistical classifier that has superior performance to classifiers currently available. Additionally, the present invention is automatically trainable, yielding improved classification performance. The present invention may be embodied in a method of statistically classifying events or objects, including the steps of gathering sets of information representative of features of an object or event; creating basic probability assignments based on said sets of information; determining a coarse information set from said sets of information; performing coarsening on said sets of information; performing linear superposition on each feature; and combining all features to reach a conclusion.

US Patent:

61253391, Sep 26, 2000

Filed:

Dec 23, 1997

Appl. No.:

8/996776

Inventors:

Kurt Reiser - Torrance CA
Yang Chen - Westlake Village CA
Todd L. Baker - Oro Valley AZ

Assignee:

Raytheon Company - Lexington MA

International Classification:

G06F10114

US Classification:

702181

Abstract:

A method providing automatic learning belief functions enabling the combination of different, and possibly contradictory information sources. The present invention provides the ability to determine erroneous information sources, inappropriate information combinations, and optimal information granularities, along with enhanced system performance.

US Patent:

20220215571, Jul 7, 2022

Filed:

Dec 20, 2021

Appl. No.:

17/556157

Inventors:

- Chicago IL, US
Leon Nguyen - Santa Ana CA, US
Fan Hung - Woodland Hills CA, US
Yang Chen - Westlake Village CA, US
Deepak Khosla - Camarillo CA, US
Haden H. Smith - Topanga CA, US

International Classification:

G06T 7/70
G06V 10/40
G06T 7/30
B64D 39/00

Abstract:

A system for refining a six degrees of freedom pose estimate of a target object based on a one-dimensional measurement includes a camera and a range-sensing device. The range-sensing device is configured to determine an actual distance measured between the range-sensing device and an actual point of intersection. The range-sensing device projects a line-of-sight that intersects with the target object at the actual point of intersection. The system also includes one or more processors in electronic communication with the camera and the range-sensing device and a memory coupled to the processors. The memory stores data into one or more databases and program code that, when executed by the processors, causes the system to predict the six degrees of freedom pose estimate of the target object. The system also determines a revised six degrees of freedom pose estimate of the target object based on at least an absolute error.

US Patent:

20210282445, Sep 16, 2021

Filed:

Mar 11, 2020

Appl. No.:

16/816178

Inventors:

Eric Jamie Wan - Hinsdale IL, US
Jason Wan - Hinsdale IL, US
Yang Chen - Hinsdale IL, US

International Classification:

A23L 33/175
C07K 14/435
C07K 14/415
A61K 9/00
A23L 33/00
A23L 33/18
A23L 33/185
A23L 33/19

Abstract:

This invention covers protein essential amino acids formulations as dietary supplements, nutritional formulations and foods that provide balanced and adequate levels of essential amino acid compositions to meet the recommended nutritional requirements for humans of different age groups and special need groups.

US Patent:

20200379486, Dec 3, 2020

Filed:

May 28, 2019

Appl. No.:

16/423892

Inventors:

- Chicago IL, US
Kevin R. Martin - Oak Park CA, US
Sean Soleyman - Calabasas CA, US
Ignacio M. Soriano - University City MO, US
Michael A. Warren - Northridge CA, US
Joshua G. Fadaie - Saint Louis MO, US
Charles Tullock - Saint Peters MO, US
Yang Chen - Westlake Village CA, US
Shawn Moffit - Glen Carbon IL, US
Calvin Chung - Saint Louis MO, US

International Classification:

G05D 1/10
G05B 13/02
G05D 1/00

Abstract:

Apparatus and methods for training a machine learning algorithm (MLA) to control a first aircraft in an environment that comprises the first aircraft and a second aircraft are described. Training of the MLA can include: the MLA determining a first-aircraft action for the first aircraft to take within the environment; sending the first-aircraft action from the MLA; after sending the first-aircraft action, receiving an observation of the environment and a reward signal at the MLA, the observation including information about the environment after the first aircraft has taken the first-aircraft action and the second aircraft has taken a second-aircraft action, the reward signal indicating a score of performance of the first-aircraft action based on dynamic and kinematic properties of the second aircraft; and updating the MLA based on the observation of the environment and the reward signal.

US Patent:

20170300788, Oct 19, 2017

Filed:

Sep 19, 2016

Appl. No.:

15/269777

Inventors:

- Malibu CA, US
Qin Jiang - Oak Park CA, US
Yang Chen - Westlake Village CA, US
Deepak Khosla - Camarillo CA, US

International Classification:

G06K 9/66
G06K 9/62
G06K 9/46
G06K 9/46
G06K 9/46
G06N 3/04
G06K 9/42

Abstract:

Described is a system for object detection in images or videos using spiking neural networks. An intensity saliency map is generated from an intensity of an input image having color components using a spiking neural network. Additionally, a color saliency map is generated from a plurality of colors in the input image using a spiking neural network. An object detection model is generated by combining the intensity saliency map and multiple color saliency maps. The object detection model is used to detect multiple objects of interest in the input image.