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Ship detection from complex background synthetic aperture radar (SAR) images is a challenging task. Due to varying local clutter and low signal-to-clutter ratio, the most conventional methods fail to yield satisfactory results. An effective ship detection approach for complex background is developed in this letter. The approach measures the local dissimilarity between target and its neighborhood by...
Relation extraction is a challenging task in biomedical text mining due to the complex of sentences in the biomedical literature. In this paper, we address multi-class relationship extraction problem from biomedical literature using Maximum Entropy model with simple word features. The proposed method is applied to extract the protein-protein interactions. Experiments show the method achieves an accuracy...
Conditional random fields (CRFs) have been used for many sequence labeling tasks and got excellent results. Further, the supervised model strongly depends on the huge training data. Active learning is a different way rather than relying on a large amount random sampling. However, random sampling constructively participates in the optimal choosing training examples. Based on different query strategies,...
Comprehensive evaluation on health care system of ten countries is discussed in this paper. In order to comprehensively assess and evaluate the health care system in an objective manner, five first-tier indicators and nineteen second-tier indicators are set up as evaluation criteria in the first place. Then entropy modeling and Matlab software are applied to compute the values for first-tier indicators...
We present a ME (Maximum Entropy) model for Semantic Chunk Annotation in a Chinese Question and Answer (Q&A) system. The model was derived from a corpus of real world questions, which are collected from some discussion groups on the Internet. The questions are supposed to be answered by other people, so the questions are very complex. The semantic chunks were introduced. Feature for the model...
This paper presents a new Chinese chunking algorithm based on conditional random fields. Conditional random fields overcome the label bias problem, model the labeling sequence and utilize many types of features. Furthermore, an algorithm of chunk similarity computation is proposed based on the systematic similarity method and semantic dictionary. The experimental results show that this approach achieves...
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