Jia Dean Li

20130172389, Jul 4, 2013

Dec 27, 2012

13/727860

Ellen Chao - Irvine CA, US
Herman Ng - Tustin CA, US
Hau Ton - Buena Park CA, US
Jia Chian Li - Irvine CA, US
Joseph S. Adorante - Irvine CA, US
Michael S. Garst - Newport Beach CA, US
Howard B. Rind - Laguna Niguel CA, US
Mark R. Hansen - San Diego CA, US
Alfred Arthur Avey - Eugene OR, US
Lloyd Jay Dolby - Eugene OR, US
Shervin Esfandiari - Eugene OR, US
Vivian R. MacKenzie - Eugene OR, US
Jeremiah Andrew Marsden - Eugene OR, US
David Charles Muchmore - Eugene OR, US

Allegan, Inc. - Irvine CA

C07D 235/12
C07D 235/08
C07D 403/12
C07D 403/06
C07D 401/12
C07D 235/14
C07D 235/06

514338, 5483101, 514394, 5483097, 5483044, 5483061, 5462734, 5483057

The present invention is directed to a compound of Formula Ior a pharmaceutically acceptable salt thereof; wherein R, R, R, R, R, m, and n are as defined herein, to pharmaceutical compositions comprising said compound, and to methods of treating diseases or conditions mediated by elevated persistent sodium current, such as an ocular disorder, multiple sclerosis, seizure disorder, and chronic pain.

20220406008, Dec 22, 2022

Jul 1, 2022

17/856720

- Santa Monica CA, US
Linjie Luo - Los Angeles CA, US
Rahul Bhupendra Sheth - Los Angeles CA, US
Jia Li - Marina Del Rey CA, US
Xutao Lv - Marina Del Rey CA, US

G06T 17/00
G06T 19/00

Systems and methods for image based location estimation are described. In one example embodiment, a first positioning system is used to generate a first position estimate. Point cloud data describing an environment is then accessed. A two-dimensional surface of an image of an environment is captured, and a portion of the image is matched to a portion of key points in the point cloud data. An augmented reality object is then aligned within one or more images of the environment based on the match of the point cloud with the image. In some embodiments, building façade data may additionally be used to determine a device location and place the augmented reality object within an image.

20220245907, Aug 4, 2022

Apr 25, 2022

17/728553

- Santa Monica CA, US
Linjie Luo - Los Angeles CA, US
Rahul Bhupendra Sheth - Los Angeles CA, US
Jia Li - Marina Del Rey CA, US
Xutao Lv - Marina Del Rey CA, US

G06T 19/00
G06T 7/73
G06V 10/10
G06V 20/00
G06V 20/10
G06V 20/20
G06F 3/01
G06F 3/04815
G06T 7/20
G06T 13/80
G06T 19/20
G06T 7/246

Systems and methods for image based location estimation are described. In one example embodiment, a first positioning system is used to generate a first position estimate. A set of structure façade data describing one or more structure façades associated with the first position estimate is then accessed. A first image of an environment is captured, and a portion of the image is matched to part of the structure façade data. A second position is then estimated based on a comparison of the structure façade data with the portion of the image matched to the structure façade data.

20230088029, Mar 23, 2023

Nov 30, 2022

18/071865

- Santa Monica CA, US
Jia Li - Marina Del Rey CA, US
Ning Xu - Irvine CA, US

G10L 25/30
G06N 3/04
H04S 7/00
G06K 9/62
G06V 20/00

An acoustic environment identification system is disclosed that can use neural networks to accurately identify environments. The acoustic environment identification system can use one or more convolutional neural networks to generate audio feature data. A recursive neural network can process the audio feature data to generate characterization data. The characterization data can be modified using a weighting system that weights signature data items. Classification neural networks can be used to generate a classification of an environment.

20210082453, Mar 18, 2021

Dec 1, 2020

17/247137

- Santa Monica CA, US
Jia Li - Marina Del Rey CA, US
Ning Xu - Irvine CA, US

G10L 25/30
G06N 3/04
G06K 9/62
G06K 9/00
H04S 7/00

An acoustic environment identification system is disclosed that can use neural networks to accurately identify environments. The acoustic environment identification system can use one or more convolutional neural networks to generate audio feature data. A recursive neural network can process the audio feature data to generate characterization data. The characterization data can he modified using a weighting system that weights signature data items. Classification neural networks can be used to generate a classification of an environment.

20210073597, Mar 11, 2021

Nov 17, 2020

16/949856

- Santa Monica CA, US
Jianchao Yang - Los Angeles CA, US
Ning Zhang - Los Angeles CA, US
Jia Li - Marina Del Rey CA, US

G06K 9/62
G06K 9/46
G06K 9/52
G06K 9/66
G06T 3/40

Systems, devices, media, and methods are presented for identifying and categorically labeling objects within a set of images. The systems and methods receive an image depicting an object of interest, detect at least a portion of the object of interest within the image using a multilayer object model, determine context information, and identify the object of interest included in two or more bounding boxes.

20200327738, Oct 15, 2020

Jun 26, 2020

16/913503

- Santa Monica CA, US
Linjie Luo - Los Angeles CA, US
Rahul Sheth - Los Angeles CA, US
Jia Li - Marina Del Rey CA, US
Xutao Lv - Marina Del Rey CA, US

G06T 19/00
G06T 7/73
G06F 3/01
G06F 3/0481
G06K 9/00
G06K 9/78
G06T 7/20
G06T 13/80
G06T 19/20
G06T 7/246

Systems and methods for image based location estimation are described. In one example embodiment, a first positioning system is used to generate a first position estimate. A set of structure façade data describing one or more structure façades associated with the first position estimate is then accessed. A first image of an environment is captured, and a portion of the image is matched to part of the structure façade data. A second position is then estimated based on a comparison of the structure façade data with the portion of the image matched to the structure façade data.

20200320353, Oct 8, 2020

Jun 17, 2020

16/946346

- Santa Monica CA, US
Kevin Dechau Tang - Los Angeles CA, US
Jianchao Yang - Los Angeles CA, US
Jia Li - Marina Del Rey CA, US

G06K 9/62
G06T 11/60

A dense captioning system and method is provided for analyzing an image to generate proposed bounding regions for a plurality of visual concepts within the image, generating a region feature for each proposed bounding region to generate a plurality of region features of the image, and determining a context feature for the image using a proposed bounding region that is a largest in size of the proposed bounding regions. For each region feature of the plurality of region features of the image, the dense captioning system and method further provides for analyzing the region feature to determine for the region feature a detection score that indicates a likelihood that the region feature comprises an actual object, and generating a caption for a visual concept in the image using the region feature and the context feature when a detection score is above a specified threshold value.