Janssen Pharmaceutica NV - New Brunswick NJ, US Frank CHAVEZ - San Diego CA, US James P. EDWARDS - San Diego CA, US Annie E. FITZGERALD - San Diego CA, US Jing LIU - San Diego CA, US Neelakandha S. MANI - San Diego CA, US Michele C. RIZZOLIO - San Diego CA, US Brad M. SAVALL - San Diego CA, US Deborah M. SMITH - San Diego CA, US Jennifer D. VENABLE - Solana Beach CA, US Jianmei WEI - San Diego CA, US Danielle K. WIENER - La Jolla CA, US Ronald L. WOLIN - San Diego CA, US
2-Aminopyrimidine compounds are described, which are useful as Hreceptor modulators. Such compounds may be used in pharmaceutical compositions and methods for the treatment of disease states, disorders, and conditions mediated by Hreceptor activity, such as allergy, asthma, autoimmune diseases, and pruritis.
2-Aminopyrimidine Modulators Of The Histamine H4 Receptor
JANSSEN PHARMACEUTICA NV - New Brunswick NJ, US Frank CHAVEZ - San Diego CA, US James P. EDWARDS - San Diego CA, US Annie E. FITZGERALD - San Diego CA, US Jing LIU - San Diego CA, US NEELAKANDHA S. MANI - San Diego CA, US Michele C. RIZZOLIO - San Diego CA, US Brad M. SAVALL - San Diego CA, US Deborah M. SMITH - San Diego CA, US Jennifer D. VENABLE - Solana Beach CA, US Jianmei WEI - San Diego CA, US Danielle K. WIENER - La Jolla CA, US Ronald L. WOLIN - San Diego CA, US
2-Aminopyrimidine compounds are described, which are useful as Hreceptor modulators. Such compounds may be used in pharmaceutical compositions and methods for the treatment of disease states, disorders, and conditions mediated by Hreceptor activity, such as allergy, asthma, autoimmune diseases, and pruritis.
High-Resolution Portrait Stylization Frameworks Using A Hierarchical Variational Encoder
Systems and method directed to an inversion-consistent transfer learning framework for generating portrait stylization using only limited exemplars. In examples, an input image is received and encoded using a variational autoencoder to generate a latent vector. The latent vector may be provided to a generative adversarial network (GAN) generator to generate a stylized image. In examples, the variational autoencoder is trained using a plurality of images while keeping the weights of a pre-trained GAN generator fixed, where the pre-trained GAN generator acts as a decoder for the encoder. In other examples, a multi-path attribute aware generator is trained using a plurality of exemplar images and learning transfer using the pre-trained GAN generator.
Image Processing Method And Apparatus For Augmented Reality, Electronic Device, And Storage Medium
- Beijing, CN - Los Angeles CA, US Xuchen SONG - Los Angeles CA, US Jianchao YANG - Los Angeles CA, US Guohui WANG - Los Angeles CA, US Zhili CHEN - Los Angeles CA, US Linjie LUO - Los Angeles CA, US Xiao YANG - Los Angeles CA, US Haoze LI - Los Angeles CA, US Jing LIU - Los Angeles CA, US
An image processing method and apparatus for augmented reality, an electronic device and a storage medium, including: acquiring a target image in response to an image acquiring instruction triggered by a user, where the target image includes a target object; acquiring an augmented reality model of the target object, and outputting the augmented reality model in combination with the target object; acquiring target audio data selected by the user, and determining an audio feature with temporal regularity according to the target audio data; and driving the augmented reality model according to the audio feature and a playing progress of the target audio data when outputting the target audio data.
Image Annotating Method, Classification Method And Machine Learning Model Training Method
- Grand Cayman, KY Peibin CHEN - Beijing, CN Weihong ZENG - Beijing, CN Xu WANG - Beijing, CN Shen SANG - Los Angeles CA, US Jing LIU - Los Angeles CA, US Chunpong LAI - Los Angeles CA, US
International Classification:
G06K 9/62
Abstract:
The present disclosure relates to an image annotating method, classification method and machine learning model training method, and to the field of computer technologies. The image annotating method includes: generating an image tag vector of image to be annotated, according to a plurality of attributes for image annotating and multiple tags corresponding to each of the attributes; annotating an image category to which the image to be annotated belongs, according to vector similarity between the image tag vector and an category tag vector of each of a plurality of image categories, the category tag vector being generated according to the multiple tags corresponding to each of the attributes.
Method And Device For Evaluating Effect Of Classifying Fuzzy Attribute
- Grand Cayman, KY Peibin CHEN - Beijing, CN Weihong ZENG - Beijing, CN Xu WANG - Beijing, CN Jing LIU - Los Angeles CA, US Chunpong LAI - Los Angeles CA, US Shen SANG - Los Angeles CA, US
International Classification:
G06K 9/00 G06K 9/62
Abstract:
A method is provided for evaluating an effect of classifying a fuzzy attribute of an object, the fuzzy attribute referring to an attribute, a boundary between two similar ones of a plurality of categories of which is blurred, wherein the method includes: generating a similarity-based ranked confusion matrix, which comprises: based on similarities of K categories of the fuzzy attribute of the object, ranking the K categories, where K is an integer greater than or equal to 2, generating a K×K all-zero initialization matrix, wherein an abscissa and an ordinate of the initialization matrix respectively represent predicted values and true values of the similarity-based ranked categories of the fuzzy attribute, and based on the true values and the predicted values of the category of the fuzzy attribute for the multiple object samples, updating values of corresponding elements in the initialization matrix; and displaying the similarity-based ranked confusion matrix.
Image Processing Method, Image Processing Device And Computer Readable Medium
- Grand Cayman, KY Weihong ZENG - Beijing, CN Peibin CHEN - Beijing, CN Xu WANG - Beijing, CN Chunpong LAI - Los Angeles CA, US Shen SANG - Los Angeles CA, US Jing LIU - Los Angeles CA, US
International Classification:
G06K 9/62 G06K 9/00 G06F 16/532
Abstract:
An image processing method includes acquiring a set of image samples for training an attribute recognition model, wherein the set of image samples includes a first subset of image samples with category labels and a second subset of image samples without category labels; training a sample prediction model using the first subset of image samples, and predicting categories of the image samples in the second subset of image samples using the trained sample prediction model; determining a category distribution of the set of image samples based on the category labels of the first subset of image samples and the predicted categories of the second subset of image samples; and acquiring a new image sample if the determined category distribution does not conform to the expected category distribution, and adding the acquired new image sample to the set of image samples.
Training Method And Device For Image Identifying Model, And Image Identifying Method
- Grand Cayman, KY Peibin CHEN - Beijing, CN Weihong ZENG - Beijing, CN Xu WANG - Beijing, CN Jing LIU - Los Angeles CA, US Chunpong LAI - Los Angeles CA, US Shen SANG - Los Angeles CA, US
International Classification:
G06V 10/764 G06V 10/82 G06V 10/72 G06N 3/08
Abstract:
The present disclosure provides a training method and device for an image identifying model, and an image identifying method. The training method comprises: obtaining image samples of a plurality of categories; inputting image samples of each category into a feature extraction layer of the image identifying model to extract a feature vector of each image sample; calculating a statistical characteristic information of an actual distribution function corresponding to each category according to the feature vector of each image sample of the each category; establishing an augmented distribution function corresponding to the each category according to the statistical characteristic information; obtaining augmented sample features of the each category based on the augmented distribution function; and inputting feature vectors of the image samples and the augmented sample features into a classification layer of the image identifying model for supervised learning.
Isbn (Books And Publications)
Advances in Natural Computation: Second International Conference, ICNC 2006, Xi'an, China, September 24-28, 2006, Proceedings, Part I
To learn more about potentially habit-forming sleep aids, we spoke to Dr. Jing Liu, OMD, PHD of Sol Nutrition. She told us that among others, melatonin and sleep aids containing antihistamines may lead to dependency. Learn more about these supplements and their potential side effects below.
Date: Apr 19, 2023
Category: Health
Source: Google
Chinese COVID-19 Vaccine Phase 2 Trial Results: Safe and Induces an Immune Response
Just like what the Terminator does in the Hollywood sci-fi film, this soft machine appears rather intelligent and can transform itself depending on the space it occupies, according to Jing Liu from the Tsinghua University This unusual behavior in robots perfectly resembles how living organisms react
Date: Mar 16, 2015
Category: Sci/Tech
Source: Google
Future T-1000 robots applaud as scientists invent self-powered liquid metal
"The soft machine looks rather intelligent and can deform itself according to the space it voyages in, just like Terminator does from the science-fiction film," explained Tsinghua University scientist Jing Liu. "These unusual behaviors perfectly resemble the living organisms in nature."
Date: Mar 12, 2015
Category: Sci/Tech
Source: Google
3-D Laser Map Shows Earthquake Zone Before and After
Other co-authors of the paper are: Austin Elliott and Peter Gold, UC Davis; J. Ramon Arrowsmith, Arizona State University; Alejandro Hinojosa Corona and J. Javier Gonzalez Garcia, CICESE, Mexico; Eric Fielding, NASA Jet Propulsion Laboratory; and Jing Liu-Zeng, Chinese Academy of Sciences.
University of Pennsylvania - TCOM, Southeast University - Computer Science & Engineering, Chengdu Foreign Languages School - Senior High School, Chengdu Foreign Languages School - Junior High School
Jing Liu
Lived:
Orange, California
Education:
Chapman University
Jing Liu
Education:
Panjin Vocational and Technical College - Communication network and equipment