Wen R Wu from Seattle, WA

Professional Records

Lawyers & Attorneys

Wen Wu - Lawyer

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Address:

(416) 591-8828 (Office)

Licenses:

New York - Delinquent 2001

Wen Wu - Lawyer

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Office:

McGraw Hill Financial, Inc.

Specialties:

Securitization
Structured Finance

ISLN:

917605114

Admitted:

2004

University:

Beijing Foreign Studies University, Beijing, China, B.A., 1997; Northwestern University, M.A., 1999

Law School:

Columbia University, J.D., 2003

Medicine Doctors

Wen S Wu

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Specialties:

Family Medicine

Education:

Md, Taipei Medical College

Resumes

Wen Wen Wu Decatur, GA

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Work:

Strategy and Management Services, Inc/Rapier Solutions, Inc

Oct 2012 to 2000
Financial Counselor
New York Life Insurance/Investment Company
Irvine, CA
Jun 2010 to Oct 2012
Financial Services Professional
Waddell & Reed, Inc
Costa Mesa, CA
Jul 2009 to Jun 2010
Financial Advisor
Waddell & Reed, Inc
Costa Mesa, CA
Jul 2009 to Jun 2010
Financial Advisor for a Securities Broker-Dealer and Investment Advisor
ACI Communications Inc
Kent, WA
Apr 2005 to Aug 2005
StemCyte Taiwan Co. Ltd

Oct 2000 to Nov 2004
Finance manager
UT Golf
Santa Ana, CA
Jun 1995 to Mar 2000
Accounting manager
Liang Jing Limited Co

Aug 1993 to Jun 1995
Accounting supervisor
Pouk & Steinle, Inc
Corona, CA
Dec 1989 to Apr 1993
Office manager
Ceromet Inc
Anaheim, CA
Aug 1987 to Dec 1989
Account

Education:

Utah State University
Logan, UT
1982 to 1987
BS in Accounting

Business Records

Name / Title

Company / Classification

Phones & Addresses

Mr. Wen Wu, DDS
Owner

Wen Wu, DDS- Family Dental
Dentists

1289 E. Hillsdale Blvd, Suite 9, Foster City, CA 94404-1294
(650) 638-9688, (650) 638-9689

Publications

Us Patents

Image-Based Tray Alignment And Tube Slot Localization In A Vision System

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US Patent:

20180045747, Feb 15, 2018

Filed:

Feb 16, 2016

Appl. No.:

15/551569

Inventors:

- Tarrytown NY, US
Patrick Wissmann - Munich, DE
Wen Wu - Kirkland WA, US
Guillaume Dumont - Paris, FR
Benjamin Pollack - Jersey City NJ, US
Terrence Chen - Princeton NJ, US

Assignee:

Siemens Healthcare Diagnostics Inc. - Tarrytown NY

International Classification:

G01N 35/00
G06T 7/00
G01N 35/04
G06T 7/73

Abstract:

A method of tube slot localization is provided using a tray coordinate system and a camera coordinate system. The method includes receiving, a series of images from at least one camera of a tray comprising tube slots arranged in a matrix of rows and columns. Each tube slot is configured to receive a sample tube. The method also includes automatically detecting fiducial markers disposed on cross sectional areas between the tube slots on the tray and receiving an encoder value indicating when each row of the tray is substantially at the center of the camera's field of view. The method further includes determining calibration information to provide mapping of locations from the tray coordinate system to locations from the camera coordinate system and automatically aligning the tray based on the encoder value and calibration information.

Image-Based Tube Slot Circle Detection For A Vision System

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US Patent:

20180047150, Feb 15, 2018

Filed:

Feb 16, 2016

Appl. No.:

15/551570

Inventors:

- Tarrytown NY, US
Wen Wu - Kirkland WA, US
Guillaume Dumont - Paris, FR
Benjamin Pollack - Jersey City NJ, US
Terrence Chen - Princeton NJ, US

Assignee:

Siemens Healthcare Diagnostics Inc. - Tarrytown NY

International Classification:

G06T 7/00
G06K 9/46
G06T 7/60
G06T 7/11
G06T 7/13

Abstract:

Embodiments provide a method of using image-based tube top circle detection that includes extracting, from one of a series of images of a tube tray, a region of interest (ROI) patch having a target tube top circle and boundaries constrained by two dimensional (2D) projections of different types of tube top circle centers. The method also includes calculating an edge gradient magnitude map of the ROI patch and constructing a three dimensional (3D) map of a circle parameter space, each location in the 3D map corresponding to a circle parameter having a center location and a diameter. The method further includes accumulating weighted votes in the 3D map from edge points in the edge gradient magnitude map along edge point gradient directions, determining locations in the 3D map as circle candidates based on the accumulated votes and selecting a target tube top circle based on the greatest accumulated votes.