Jia Wei Xu

20220245470, Aug 4, 2022

Jun 5, 2021

17/339985

- San Ramon CA, US
Jia Xu - Tiburon CA, US
Jim Gehrett - Larkspur CA, US

Asserts Inc. - San Ramon CA

G06N 5/02
H04L 29/08

A system that automatically monitors an application without requiring administrators to manually identify what portions of the application should be monitored. The present system is flexible in that it can be deployed in several different environments having different operating parameters and nomenclature. The present application is able to automatically monitor applications in the different environments, and convert data, metric, and event nomenclature of the different environments to a universal nomenclature. A system graph is then created from the nodes and metrics of each environment application that make up a client system. The system graph, and the properties of entities within the graph, can be displayed through an interface to a user.

20220245476, Aug 4, 2022

Jun 5, 2021

17/339988

- San Ramon CA, US
Jia Xu - Tiburon CA, US
Jim Gehrett - Larkspur CA, US

Asserts Inc. - San Ramon CA

G06N 5/02
G06N 5/04

A system monitors an application and automatically models, correlates, and presents insights. The monitoring is performed without requiring administrators to manually identify what portions of the application should be monitored. The modeling and correlating are performed using a knowledge graph and automated modeling system that identifies system entities, builds the knowledge graph, and reports the most crucial insights, determined automatically, using a dashboard that automatically reports on the most relevant system data and status.

20190005603, Jan 3, 2019

Jun 30, 2017

15/639000

- Santa Clara CA, US
Jia Xu - Santa Clara CA, US
Vladlen Koltun - Santa Clara CA, US

INTEL CORPORATION - Santa Clara CA

G06T 1/20
G06T 5/00

Techniques are provided for approximating image processing functions using convolutional neural networks (CNNs). A methodology implementing the techniques according to an embodiment includes performing, by a CNN, a sequence of non-linear operations on an input image to generate an output image. The generated output image approximates the application of a targeted image processing operator to the input image. The CNN is trained on pairs of training input and output images, wherein the training output images are generated by application of the targeted image processing operator to the training input images. The CNN training process generates bias parameters and convolutional kernel parameters to be employed by the CNN for processing of intermediate image layers associated with processing stages between the input image and the output image, each of the processing stages associated with one of the sequence of non-linear operations. The parameters are associated with the targeted image processing operator.

20170034030, Feb 2, 2017

Jul 31, 2015

14/815205

- San Francisco CA, US
Jia Xu - San Rafael CA, US
Binil Thomas - Walnut Creek CA, US

H04L 12/26
H04L 29/08

A system monitors applications that provide a single content page by monitoring network traffic associated with single page transitions. The network traffic may be monitored by mechanisms provided by a network browser that updates the page. Updates to the page, called transitions, may be detected when they first begin. The network traffic associated with a single page transition from a first content page to a second version of that content page may be tracked through the network traffic viewing mechanism. When the network traffic is determined to have concluded, the end of the single content page transition is determined to have occurred. Metrics may then be generated from data collected during the transition, and the data and metrics may be reported to a controller.