International Business Machines Corporation

Boliang Chen

Dong Sheng Li

Junchi Yan

Chao Zhang

Min Gong

Jing Chang Huang

Feng Cao

Stephen Mingyu Chu

Wei Peng Zhang

Weipeng Zhang

Zheng Yu

Techniques for model based data processing are proposed. In one example, a computer-implemented method is as follows. A first model is determined from a first category of data processing models and a second model is determined from a second category of data processing models. The second category can be different from the first category in some instances. Performance of a first combined model of the first and second models can be compared with performance of the first model. A target model for processing data can be selected from the first combined model and the first model based on the comparing.

Model based data processing

Embedding representation for a document is generated based on clustering words in the document. Representative clusters are selected and a weighted sum of the embeddings of the words in the selected clusters is determined as a document embedding. Documents are labeled based on document embeddings. A machine learning algorithm is trained using the documents. The machine learning algorithm predicts a label of a given document based on the given document's document embedding.

Event clustering and classification with document embedding

A computer-implemented method, computer program product, and system for detecting work-piece defects. The computer-implemented method may include: receiving a first image of a training work-piece captured using a non-destructive imaging process and a second image of the training work-piece captured using a destructive imaging process; receiving an image of a work-piece captured using a non-destructive imaging process, wherein the work-piece is substantially similar to the training work-piece, and the non-destructive imaging process used to capture the work-piece is substantially similar to the non-destructive imaging process used to capture the training work-piece; matching the image of the work-piece to the first image of the training work-piece; and enhancing the image of the work-piece using the second image of the training work-piece, in response to the image of the work-piece matching the first image of the training work-piece.

Work-piece defect inspection via optical images and CT images

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Shanghai, China

Boliang Chen