Guang N Chen

US Patent:

20050233337, Oct 20, 2005

Filed:

Apr 19, 2004

Appl. No.:

10/828357

Inventors:

Bill Peck - Mountain View CA, US
Eric Leproust - San Jose CA, US
David Adaskin - San Jose CA, US
Guang Chen - San Jose CA, US
William Chesk - San Jose CA, US
Donald Schremp - San Jose CA, US
Stanley Woods - Cupertino CA, US

International Classification:

C12Q001/68
C12M001/34
B05D003/00

US Classification:

435006000, 435287200, 427002110

Abstract:

Methods and devices for fabricating a chemical array are provided. Embodiments include determining a chemical array layout in which each feature in the layout has a size that is chosen based on its composition and fabricating a chemical array according to the chemical array layout. In certain embodiments, at least two features of an array fabricated according to the subject methods are of different sizes. Embodiments also include chemical arrays having features of different sizes, e.g., fabricated according to the subject methods. Also provided are embodiments that include fluid deposition devices capable of fabricating chemical arrays having features of different sizes, e.g., for use in practicing the subject methods. Algorithms present on computer readable mediums for use in practicing the subject methods may also be provided in certain embodiments. Embodiments of the subject invention may also include systems and kits for use in practicing the subject methods.

US Patent:

20220335190, Oct 20, 2022

Filed:

Jul 1, 2022

Appl. No.:

17/856776

Inventors:

Guang Chen - Fremont CA, US
Yuet Li - Fremont CA, US
Archanna Srinivasan - San Jose CA, US

International Classification:

G06F 30/347

Abstract:

Systems or methods of the present disclosure may provide for determining a load line for operation of a programmable logic fabric where the load line is based at least in part on design configuration details for a design or a configuration rather for generic deployment of the programmable logic device. The load line may be determined using software modeling for the design or configuration. Additionally or alternatively, the load line may be determined using runtime testing and sensing of real-world parameters. This determination based on real-world parameters of a deployment of the configuration or design is based on a determination of a step load for the design or configuration.

US Patent:

20210313989, Oct 7, 2021

Filed:

Jun 21, 2021

Appl. No.:

17/353549

Inventors:

- Santa Clara CA, US
Guang Chen - Fremont CA, US
Venu Kondapalli - San Jose CA, US

Assignee:

Intel Corporation - Santa Clara CA

International Classification:

H03K 19/1778
H03K 21/08

Abstract:

An integrated circuit includes a first voltage decrease detection circuit that has a first comparator circuit that compares a supply voltage in the integrated circuit to a threshold voltage to generate a first detection signal that indicates a decrease in the supply voltage, and a first timestamp storage circuit that stores a first timestamp in response to the first detection signal indicating the decrease. The integrated circuit includes a second voltage decrease detection circuit that has a second comparator circuit that compares the supply voltage to the threshold voltage to generate a second detection signal that indicates the decrease, and a second timestamp storage circuit that stores a second timestamp in response to the second detection signal indicating the decrease. The integrated circuit includes a control circuit that determines a location of a source of the decrease in the integrated circuit based on the first and the second timestamps.

US Patent:

20210004643, Jan 7, 2021

Filed:

Jul 2, 2019

Appl. No.:

16/460192

Inventors:

- Sunnyvale CA, US
Guang CHEN - Sunnyvale CA, US
Weide ZHANG - Sunnyvale CA, US
Yuliang GUO - Sunnyvale CA, US
Ka Wai TSOI - Sunnyvale CA, US

International Classification:

G06K 9/62
G06K 9/00

Abstract:

A list of images is received. The images were captured by a sensor of an ADV chronologically while driving through a driving environment. A first image of the images is identified that includes a first object in a first dimension (e.g., larger size) detected by an object detector using an object detection algorithm. In response to the detection of the first object, the images in the list are traversed backwardly in time from the first image to identify a second image that includes a second object in a second dimension (e.g., smaller size) based on a moving trail of the ADV represented by the list of images. The second object is then labeled or annotated in the second image equivalent to the first object in the first image. The list of images having the labeled second image can be utilized for subsequent object detection during autonomous driving.

US Patent:

20200406893, Dec 31, 2020

Filed:

Jun 28, 2019

Appl. No.:

16/457847

Inventors:

- Sunnyvale CA, US
Guang CHEN - Sunnyvale CA, US
Weide ZHANG - Sunnyvale CA, US
Yuliang GUO - Sunnyvale CA, US
Ka Wai TSOI - Sunnyvale CA, US

International Classification:

B60W 30/095
B60W 30/09
G06K 9/00
G05D 1/00

Abstract:

During the autonomous driving, the movement trails or moving history of obstacles, as well as, an autonomous driving vehicle (ADV) may be maintained in a corresponding buffer. For each of the obstacles or objects and the ADV, the vehicle states at different points in time are maintained and stored in one or more buffers. The vehicle states representing the moving trails or moving history of the obstacles and the ADV may be utilized to reconstruct a history trajectory of the obstacles and the ADV, which may be used for a variety of purposes. For example, the moving trails or history of obstacles may be utilized to determine lane configuration of one or more lanes of a road, particularly, in a rural area where the lane markings are unclear. The moving history of the obstacles may also be utilized predict the future movement of the obstacles, tailgate an obstacle, and infer a lane line.

US Patent:

20200410252, Dec 31, 2020

Filed:

Jun 28, 2019

Appl. No.:

16/457820

Inventors:

- Sunnyvale CA, US
Tae Eun CHOE - Sunnyvale CA, US
Yuliang GUO - Sunnyvale CA, US
Guang CHEN - Sunnyvale CA, US
Weide ZHANG - Sunnyvale CA, US

International Classification:

G06K 9/00
G06K 9/62

Abstract:

In one embodiment, a set of bounding box candidates are plotted onto a 2D space based on their respective dimension (e.g., widths and heights). The bounding box candidates are clustered on the 2D space based on the distribution density of the bounding box candidates. For each of the clusters of the bounding box candidates, an anchor box is determined to represent the corresponding cluster. A neural network model is trained based on the anchor boxes representing the clusters. The neural network model is utilized to detect or recognize objects based on images and/or point clouds captured by a sensor (e.g., camera, LIDAR, and/or RADAR) of an autonomous driving vehicle.

US Patent:

20200410255, Dec 31, 2020

Filed:

Jun 28, 2019

Appl. No.:

16/457557

Inventors:

- Sunnyvale CA, US
Tae Eun Choe - Sunnyvale CA, US
Ka Wai Tsoi - Sunnyvale CA, US
Guang Chen - Sunnyvale CA, US
Weide Zhang - Sunnyvale CA, US

International Classification:

G06K 9/00
G06T 7/536
G06N 3/08
G06K 9/62

Abstract:

In some implementations, a method is provided. The method includes obtaining an image depicting an environment where an autonomous driving vehicle (ADV) may be located. The image comprises a plurality of line indicators. The plurality of line indicators represent one or more lanes in the environment. The image is part of training data for a neural network. The method also includes determining a plurality of line segments based on the plurality of line indicators. The method further includes determining a vanishing point within the image based on the plurality of line segments. The method further includes updating one or more of the image or metadata associated with the image to indicate a location of the vanishing point within the image.

US Patent:

20200410260, Dec 31, 2020

Filed:

Jun 28, 2019

Appl. No.:

16/457719

Inventors:

- Sunnyvale CA, US
Yuliang GUO - Sunnyvale CA, US
Guang CHEN - Sunnyvale CA, US
Weide ZHANG - Sunnyvale CA, US
Ka Wai TSOI - Sunnyvale CA, US

International Classification:

G06K 9/00
G06T 11/20
G05D 1/00
G05D 1/02
B60W 30/09

Abstract:

In one embodiment, in addition to detecting or recognizing an actual lane, a virtual lane is determined based on the current state or motion prediction of an ADV. A virtual lane may or may not be identical or similar to the actual lane. A virtual lane may represent the likely movement of the ADV in a next time period given the current speed and heading direction of the vehicle. If an object is detected that may cross a lane line of the virtual lane and is a closest object to the ADV, the object is considered as a CIPO, and an emergency operation may be activated. That is, even though an object may not be in the path of an actual lane, if the object is in the path of a virtual lane of an ADV, the object may be considered as a CIPO and subject to a special operation.