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The precise named entity recognition (NER) is a key component in Chinese clinical natural language processing. Although clinical NER systems have attracted widespread attention and been studied for decades, the latest NER research usually relies on a shallow text representation with one‐layer neural encoding, which fails to capture deep features and limits its performance improvement. To capture more...
Deep learning has become increasingly popular in both academic and industrial areas in the past years. Various domains including pattern recognition, computer vision, and natural language processing have witnessed the great power of deep networks. However, current studies on deep learning mainly focus on data sets with balanced class labels, while its performance on imbalanced data is not well examined...
In order to picture the complexity of software architecture, class collaboration network is defined to abstract the architecture of object-oriented software on class level. Eclipse is selected as example of object-oriented software, and its class collaboration network is constructed and the degree distribution of the network is analyzed by statistical physics with the conclusion that degree-rank,...
Recognition for arcs is an important and difficult problem in the study on engineering drawings vectorization. This paper presents an algorithm for recognizing arcs using bar tracking, which acquires the points chains of arcs and combined lines using bar tracking, then the combined lines are segmented, at last the arcs are fitted and validated. In experiments, we test the algorithm using benchmark...
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