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Su Feng Chen

age ~72

from Tracy, CA

Also known as:
  • Su F Chen
  • Yueh Su Chen
  • Yueh S Chen
  • Yueh Su Feng Chen
  • Yueh Feng Chen
  • Yueh F Chen
  • Yueh N
  • G Chen
  • Sufeng Chen
  • Yue Chen
Phone and address:
964 Gotland Ct, Tracy, CA 95376

Su Chen Phones & Addresses

  • 964 Gotland Ct, Tracy, CA 95376
  • Saratoga, CA
  • Waianae, HI
  • Sunnyvale, CA
  • San Jose, CA
  • Riverside, CA
  • Hamilton, OH
  • Houston, TX
  • Minneapolis, MN

Medicine Doctors

Su Chen Photo 1

Su H Chen, Palo Alto CA - MFT

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Specialties:
Marriage & Family Therapy
Address:
430 Sherman Ave Suite 203, Palo Alto, CA 94306
Languages:
English
Su Chen Photo 2

Su Hsiu Chen, Palo Alto CA

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Specialties:
Psychologist
Address:
430 Sherman Ave, Palo Alto, CA 94306
Name / Title
Company / Classification
Phones & Addresses
Su Chen
Principal
Menlo Bbq
Eating Place
555 Willow Rd, Menlo Park, CA 94025
(650)3216188
Su Chen
Principal, Psychologist
Su Hsiu Chen Mft
College/University
430 Sherman Ave, Palo Alto, CA 94306
Su L. Chen
Manager
Grace's Hallmark
Ret Gifts/Novelties · Gift Shops
1560 Stoneridge Mall Rd, Pleasanton, CA 94588
(925)4631915, (925)4167708

Us Patents

  • Distributed Computing Document Recognition And Processing

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  • US Patent:
    6742161, May 25, 2004
  • Filed:
    Mar 7, 2000
  • Appl. No.:
    09/520892
  • Inventors:
    Barnaby James - Los Gatos CA
    Su Chen - San Jose CA
  • Assignee:
    ScanSoft, Inc. - Peabody MA
  • International Classification:
    G06F 1721
  • US Classification:
    715500, 715530
  • Abstract:
    The present invention is a system and method for performing document recognition and processing in a distributed computing environment. The invention uses applications which are remotely located from one or more users and may be accessed via a network. One or more users utilize terminals including computers, facsimile machines, and/or scanners to transmit documents to be processed to a network or a network server which in turn transmits the documents to various computer software applications which process the documents at a network processing location. Once the documents have been processed, the processed documents are transmitted to the users according to one or more preferences associated with a user identification and/or authentication which may be determined by either a network server or an application server. Users utilizing a computer terminal make use of various data transfer programs capable of transferring document data over a network to an application server at a remote location and receiving processed document data via a network.
  • Method And Apparatus Of Data Compression For Computer Networks

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  • US Patent:
    7558290, Jul 7, 2009
  • Filed:
    Dec 16, 2005
  • Appl. No.:
    11/303651
  • Inventors:
    Antonio Nucci - Burlingame CA, US
    Su Chen - Somerset NJ, US
  • Assignee:
    Narus, Inc. - Sunnyvale CA
  • International Classification:
    H04J 3/18
  • US Classification:
    370477
  • Abstract:
    An important component of network monitoring is to collect traffic data which is a bottleneck due to large data size. We introduce a new table compression method called “Group Compression” to address this problem. This method uses a small training set to learn the relationship among columns and group them; the result is a “compression plan”. Based on this plan, each group is compressed separately. This method can reduce the compressed size to 60%-70% of the IP flow logs compressed by GZIP.
  • System And Method For Network Data Compression

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  • US Patent:
    8516157, Aug 20, 2013
  • Filed:
    Apr 20, 2011
  • Appl. No.:
    13/091090
  • Inventors:
    Antonio Nucci - San Jose CA, US
    Su Chen - Somerset NJ, US
  • Assignee:
    Narus, Inc. - Sunnyvale CA
  • International Classification:
    G06F 15/16
    H04J 3/18
  • US Classification:
    709247, 709246, 370477
  • Abstract:
    The present invention relates to a method of compressing data in a network, the data comprising a plurality of packets each having a header and a payload, the header comprising a plurality of header fields, the method comprising generating a classification tree based on at least a portion of the plurality of header fields, determining a inter-packet compression plan based on the classification tree, and performing inter-packet compression in real time for each payload of at least a first portion of the plurality of packets, the inter-packet compression being performed according to at least a portion of the inter-packet compression plan.
  • System And Method For Network Data Compression

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  • US Patent:
    8046496, Oct 25, 2011
  • Filed:
    Dec 12, 2007
  • Appl. No.:
    11/955259
  • Inventors:
    Antonio Nucci - San Jose CA, US
    Su Chen - Sunnyvale CA, US
  • Assignee:
    Narus, Inc. - Sunnyvale CA
  • International Classification:
    G06F 15/16
    H04J 3/18
  • US Classification:
    709247, 709246, 370477
  • Abstract:
    The present invention relates to a method of compressing data in a network, the data comprising a plurality of packets each having a header and a payload, the header comprising a plurality of header fields, the method comprising generating a classification tree based on at least a portion of the plurality of header fields, determining a inter-packet compression plan based on the classification tree, and performing inter-packet compression in real time for each payload of at least a first portion of the plurality of packets, the inter-packet compression being performed according to at least a portion of the inter-packet compression plan.
  • Generating Deep Harmonized Digital Images

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  • US Patent:
    20220292654, Sep 15, 2022
  • Filed:
    Mar 12, 2021
  • Appl. No.:
    17/200338
  • Inventors:
    - San Jose CA, US
    Yifan Jiang - Austin TX, US
    Yilin Wang - San Jose CA, US
    Jianming Zhang - Campbell CA, US
    Kalyan Sunkavalli - San Jose CA, US
    Sarah Kong - Cupertino CA, US
    Su Chen - San Jose CA, US
    Sohrab Amirghodsi - Seattle WA, US
    Zhe Lin - Fremont CA, US
  • International Classification:
    G06T 5/50
    G06T 7/194
    G06T 11/60
    G06T 11/00
    G06N 3/04
    G06N 3/08
  • Abstract:
    The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately, efficiently, and flexibly generating harmonized digital images utilizing a self-supervised image harmonization neural network. In particular, the disclosed systems can implement, and learn parameters for, a self-supervised image harmonization neural network to extract content from one digital image (disentangled from its appearance) and appearance from another from another digital image (disentangled from its content). For example, the disclosed systems can utilize a dual data augmentation method to generate diverse triplets for parameter learning (including input digital images, reference digital images, and pseudo ground truth digital images), via cropping a digital image with perturbations using three-dimensional color lookup tables (“LUTs”). Additionally, the disclosed systems can utilize the self-supervised image harmonization neural network to generate harmonized digital images that depict content from one digital image having the appearance of another digital image.
  • Generating Depth Images Utilizing A Machine-Learning Model Built From Mixed Digital Image Sources And Multiple Loss Function Sets

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  • US Patent:
    20220284613, Sep 8, 2022
  • Filed:
    Feb 26, 2021
  • Appl. No.:
    17/186436
  • Inventors:
    - San Jose CA, US
    Jianming Zhang - Campbell CA, US
    Oliver Wang - Seattle WA, US
    Simon Niklaus - San Jose CA, US
    Mai Long - Portland OR, US
    Su Chen - San Jose CA, US
  • International Classification:
    G06T 7/593
    G06T 7/30
    G06T 7/13
    G06T 7/143
    G01S 17/894
    G01S 17/42
  • Abstract:
    This disclosure describes one or more implementations of a depth prediction system that generates accurate depth images from single input digital images. In one or more implementations, the depth prediction system enforces different sets of loss functions across mix-data sources to generate a multi-branch architecture depth prediction model. For instance, in one or more implementations, the depth prediction model utilizes different data sources having different granularities of ground truth depth data to robustly train a depth prediction model. Further, given the different ground truth depth data granularities from the different data sources, the depth prediction model enforces different combinations of loss functions including an image-level normalized regression loss function and/or a pair-wise normal loss among other loss functions.
  • Reconstructing Three-Dimensional Scenes Portrayed In Digital Images Utilizing Point Cloud Machine-Learning Models

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  • US Patent:
    20220277514, Sep 1, 2022
  • Filed:
    Feb 26, 2021
  • Appl. No.:
    17/186522
  • Inventors:
    - San Jose CA, US
    Jianming Zhang - Campbell CA, US
    Oliver Wang - Seattle WA, US
    Simon Niklaus - San Jose CA, US
    Mai Long - Portland OR, US
    Su Chen - San Jose CA, US
  • International Classification:
    G06T 17/00
    G06K 9/00
    G06N 3/04
    G06T 7/80
  • Abstract:
    This disclosure describes implementations of a three-dimensional (3D) scene recovery system that reconstructs a 3D scene representation of a scene portrayed in a single digital image. For instance, the 3D scene recovery system trains and utilizes a 3D point cloud model to recover accurate intrinsic camera parameters from a depth map of the digital image. Additionally, the 3D point cloud model may include multiple neural networks that target specific intrinsic camera parameters. For example, the 3D point cloud model may include a depth 3D point cloud neural network that recovers the depth shift as well as include a focal length 3D point cloud neural network that recovers the camera focal length. Further, the 3D scene recovery system may utilize the recovered intrinsic camera parameters to transform the single digital image into an accurate and realistic 3D scene representation, such as a 3D point cloud.
  • Utilizing A Segmentation Neural Network To Process Initial Object Segmentations And Object User Indicators Within A Digital Image To Generate Improved Object Segmentations

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  • US Patent:
    20220198671, Jun 23, 2022
  • Filed:
    Dec 18, 2020
  • Appl. No.:
    17/126986
  • Inventors:
    - San Jose CA, US
    Su Chen - San Jose CA, US
    Shuo Yang - Bloomington IN, US
  • International Classification:
    G06T 7/11
    G06T 7/143
    G06T 7/136
    G06T 7/162
    G06T 7/90
    G06N 3/08
    G06N 3/04
  • Abstract:
    The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize a deep neural network to process object user indicators and an initial object segmentation from a digital image to efficiently and flexibly generate accurate object segmentations. In particular, the disclosed systems can determine an initial object segmentation for the digital image (e.g., utilizing an object segmentation model or interactive selection processes). In addition, the disclosed systems can identify an object user indicator for correcting the initial object segmentation and generate a distance map reflecting distances between pixels of the digital image and the object user indicator. The disclosed systems can generate an image-interaction-segmentation triplet by combining the digital image, the initial object segmentation, and the distance map. By processing the image-interaction-segmentation triplet utilizing the segmentation neural network, the disclosed systems can provide an updated object segmentation for display to a client device.

Resumes

Su Chen Photo 3

Su Chen

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Su Chen Photo 4

Su Chen

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Su Chen Photo 5

Su Chen

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Su Chen Photo 6

Manager

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Work:
Chinamobiletech
Manager
Su Chen Photo 7

Su Qiong Chen

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Su Chen Photo 8

Su Chen

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Skills:
Biotechnology
Ems
Su Chen Photo 9

Su Chin Chen

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Su Chen Photo 10

Su Chen

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Youtube

Modern Warfare2: HC Suchen & Zerstren mit AK-...

Hallo und herzlich Willkommen, heute gibt es zwei Commentaries in eine...

  • Category:
    Gaming
  • Uploaded:
    10 Oct, 2010
  • Duration:
    14m 34s

Tokio Hotel Menschen suchen menschen Live.

(human Connect to human) Mtv Live in Athens. Enjoy? :D

  • Category:
    Entertainment
  • Uploaded:
    09 Nov, 2009
  • Duration:
    3m 50s

Chakuza - Eines Tages [ Suchen & Zerstren 2 ]

Das Offizielle Lied von Chakuza!!! *Gute Quallitt*

  • Category:
    Music
  • Uploaded:
    29 Nov, 2010
  • Duration:
    3m 1s

Chakuza - Suchen und Zerstren 2 Snippet

Chakuza - Suchen und Zerstren 2 (03.12.10) 1.Intro 2.Sorry 3.Teufelsgi...

  • Category:
    Music
  • Uploaded:
    03 Dec, 2010
  • Duration:
    6m 30s

Sam Nolte - Menschen Suchen Menschen (Tokio H...

As the intro says, all audio was created on garage band. I decided to ...

  • Category:
    Music
  • Uploaded:
    22 Apr, 2010
  • Duration:
    4m 28s

Chakuza - Suchen & Zerstren 2

Neues Chakuza Album, Suchen & Zerstren 2. Ab dem 3.Dezember im Laden!

  • Category:
    Music
  • Uploaded:
    01 Nov, 2010
  • Duration:
    3m 51s

Menschen Suchen Menschen Tokio Hotel - Prague...

Menschen Suchen Menschen

  • Category:
    Entertainment
  • Uploaded:
    16 Mar, 2010
  • Duration:
    3m 33s

Tokio Hotel Menschen Suchen Menschen (Lyrics...

Tokio Hotel - Menschen Suchen Menschen (Lyrics HD) Lyrics: Im Traum Im...

  • Category:
    Music
  • Uploaded:
    02 Jan, 2010
  • Duration:
    3m 21s

Myspace

Su Chen Photo 11

Su Chen

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Locality:
, China
Gender:
Female
Birthday:
1952
Su Chen Photo 12

Su Chen

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Locality:
Perry Hall, Maryland
Gender:
Female
Birthday:
1940
Su Chen Photo 13

Su Chen

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Locality:
changsha,
Gender:
Female
Birthday:
1947
Su Chen Photo 14

Su Chen

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Locality:
China
Gender:
Male
Birthday:
1946

Plaxo

Su Chen Photo 15

Ms. Joyce W.H. Chen Su

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Taipei Taiwan

Flickr

Facebook

Su Chen Photo 24

Su Chen Fg

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Su Chen Fong
Su Chen Photo 25

Su You Chen

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Su Chen Photo 26

Su Pin Chen

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Su Chen Photo 27

Su Yang Chen

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Su Chen Photo 28

Su Park Chen

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Su Chen Photo 29

Su Pin Chen

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Su Chen Photo 30

Su Yun Chen

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Su Chen Photo 31

Su Yen Chen

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Googleplus

Su Chen Photo 32

Su Chen

Work:
UCLA
Su Chen Photo 33

Su Chen

Su Chen Photo 34

Su Chen

Su Chen Photo 35

Su Chen

Su Chen Photo 36

Su Chen

Su Chen Photo 37

Su Chen

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Su Chen

Su Chen Photo 39

Su Chen

Classmates

Su Chen Photo 40

Su Chen

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Schools:
University of Denver at DCB Denver CO 1999-2003
Community:
Virginia Mann, Stephen Raydon
Su Chen Photo 41

Chen Su, South China Univ...

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Su Chen Photo 42

Torrance High School, Tor...

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Graduates:
Su Chen (1980-1984),
Joseph Kueneman (1974-1978),
susan miller (1984-1988),
Dick Smart (1951-1955)
Su Chen Photo 43

South China University, G...

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Graduates:
Chen Su (2002-2006),
Zheng Zhang (1988-1992),
Jasen Chen (2000-2004),
Hongqiang Hongqiang (2000-2004)

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