Ming Dean Yang

US Patent:

7149483, Dec 12, 2006

Filed:

Oct 28, 2003

Appl. No.:

10/695226

Inventors:

William Reinisch - New York NY, US
Ming Yang - Princeton Junction NJ, US
Haim Harel - New York NY, US

Assignee:

Magnolia Broadband Inc. - Bedminster NJ

International Classification:

H03C 7/02
H04B 1/02
H04B 7/00

US Classification:

455101, 455103, 455 91

Abstract:

A method for amplifying diversity transmit signals includes receiving a transmit signal at a vector modulator, where the vector modulator processes the transmit signal to yield diversity transmit signals, amplifying each of the diversity transmit signals according to a gain using at least one power amplifier, and transmitting the amplified diversity transmit signals at a plurality of antennas.

US Patent:

20210279817, Sep 9, 2021

Filed:

Feb 8, 2021

Appl. No.:

17/170414

Inventors:

- Menlo Park CA, US
Liu Liu - Marina Del Rey CA, US
Lubomir Dimitrov Bourdev - Mountain View CA, US
Robert D. Fergus - New York NY, US
Ming Yang - Orlando FL, US

International Classification:

G06Q 50/00
G06N 20/00

Abstract:

Systems, methods, and non-transitory computer-readable media can receive a compressed convolutional neural network (CNN). A media content item to be processed can be acquired. The compressed CNN to can be utilized to apply a media processing technique to the media content item to produce information about the media content item. It can be determined, based on at least some of the information about the media content item, whether to transmit at least a portion of the media content item to one or more remote servers for additional media processing.

US Patent:

20170132511, May 11, 2017

Filed:

Dec 29, 2015

Appl. No.:

14/982874

Inventors:

- Menlo Park CA, US
Liu Liu - Marina Del Rey CA, US
Lubomir Bourdev - Mountain View CA, US
Ming Yang - Foster City CA, US
Robert D. Fergus - New York NY, US

International Classification:

G06N 3/08
G06Q 50/00

Abstract:

Systems, methods, and non-transitory computer-readable media can receive a compressed convolutional neural network (CNN). A media content item to be processed can be acquired. The compressed CNN to can be utilized to apply a media processing technique to the media content item to produce information about the media content item. It can be determined, based on at least some of the information about the media content item, whether to transmit at least a portion of the media content item to one or more remote servers for additional media processing.