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For the 2D radar system, in order to improve the performance of target plots, a new algorithm based on geometric center and amplitudes of measurements was proposed, aimed at that the traditional plots centroid algorithm does not use the amplitude information or over-uses it. The proposed algorithm can reduce the weights of the measurements which are far away from the geometric centre, so as to obtain...
Object detection is an important part of computer vision research, which directly affects the follow-on object identification and tracking, analysis and understanding of the scene. In this paper, based on scale space theory and the SIFT feature matching algorithm, we propose a method to create a SIFT vector field. Through four different application scenarios we demonstrate the value of building a...
Micorarray data are often extremely asymmetric in dimensionality, such as thousands or even tens of thousands of genes and a few hundreds of samples. Such extreme asymmetry between the dimensionality of genes and samples can lead inaccurate diagnosis of disease in clinic. Therefore, it has been shown that selecting a small set of marker genes can lead to improved classification accuracy. In this paper,...
This paper presents an implementation of incremental tumor diagnosis algorithm (ITDA) on microarray data for improving diagnostic accuracy of tumor. A classifier (BP or KNN) was used in the algorithm to estimate confidences of a new unlabeled sample in different classes. When one confidence is higher than the threshold, the sample will be labeled; otherwise, the sample will be diagnosed by medical...
MAXQ is a new framework for multi-agent reinforcement learning. But the MAXQ framework cannot decompose all subtasks into more refined hierarchies and the hierarchies are difficult to be discovered automatically. In this paper, a multi-agent hierarchical reinforcement learning approach, named OptMAXQ, by integrating Options into MAXQ is presented. In the OptMAXQ framework, the MAXQ framework is used...
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