International Business Machines Corporation

Xu Min

Dan Zhang

Yi Qin Yu

Jing Mei

Hong Bing Zhang

Shao Chun Li

Shiwan Zhao

Fan Li

Xue Ping Liu

Yuan Yuan Ding

Yuan Zhou

Chao Xin

Zhong Fang Yuan

Tong Liu

Yi Chen Zhong

Yan Fei Wang

Embodiments of the present disclosure relate to a method, system, and computer program product for domain adaptation. According to the method, a source model of a source domain is obtained, where the source model is trained to generate a label indicating a predicted category of data from the source domain. A training sample from a target domain is obtained, where the training sample comprises training data from the target domain and a true label indicating a true category of the training data from the target domain. A first label is generated for the training data by using the source model. The first label indicates a predicted category of the training data. A target model of the target domain is trained based on the training data, the true label and the first label.

Domain adaptation

In an aspect for generating a 2-dimensional (2D) building mapping, a computer-implemented method may include one or more processors configured for receiving scanning data in a first file format corresponding to 3-dimensional (3D) aerial Light Detection and Ranging (LiDaR) images. Further, the method may include transforming the first file format to a second file format and transmitting the scanning data to a building semantic segmentation component. Further, the computer-implemented method may include generating semantic segmentation data corresponding to building structures defined by point clusters; generating instance segmentation data corresponding to top surfaces of the building structures; generating building boundary data for each one of the point clusters based on one or more of the semantic segmentation data and the instance segmentation data; and processing the building boundary data to generate a 2D building mapping comprising refined boundary lines for each of the point clusters.

Generating 2D mapping using 3D data

Analysis of edge closures of metal surface particles based on a graph structure.

Analyzing edge closures of metal surface particles based on graph structures

The present disclosure relates to a method, system and computer program product for electronic health record (EHR) data synthetization. According to the method, an original EHR dataset X is captured. A latent space Z is generated from the original EHR dataset X, wherein dimensionality of Z is lower than that of X. A stochastic process prior module is applied to the latent space Z. Synthetic EHR dataset X' is reconstructed from the latent space Z after being applied with the stochastic process prior.

Electronic health record data synthesization

An approach is provided in which the approach receives an image that includes multiple image points and constructs a plane in the image based on a first subset of the plurality of image points. The approach identifies a second subset of the image points that belong to the plane and are not part of the first subset of image points, and removes the first subset of image points and the second subset of image points form the image points. The approach annotates the remaining subset of image points in the image.

Three-dimensional segmentation annotation

Aspects of the invention include a computer-implemented method including extracting a domain-specific object feature from a first image data, wherein the feature describes an object in the first image data. A domain-specific semantic meaning of text data is determined. The object feature is mapped to a portion of the text data, wherein the portion of the text data describes the object. A joint representation of the object and the portion of the text data is created. A second image data and a query directed towards an object in the second image data is received. An answer to the query is generated based on the joint representation.

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Beijing, China

Xu Min