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This paper reviews recent advances of sparse solution methods for solving inverse problems in antennas and propagation. Mathematical formulation of sparse solution methods is first presented. Typical applications are then introduced, including direction of arrival estimation, extrapolation of electromagnetic signals, array diagnosis, and array beamforming. It is shown that, by utilizing the a priori...
In this paper, we proposed a biased support vector machine (Biased-SVM) with self-constructed Universum (termed as U-BSVM) to solve the PU learning problem. We first treat the PU problem as an imbalanced binary classification problem by labeling all the unlabeled inputs as negative with noise, then inspired by the Universum-SVM (U-SVM), introduce the Universum data set which is constructed from the...
In this paper, we propose to apply the nonparallel support vector machine (NPSVM) for positive and unlabeled learning problem(PU learning problem) in which only a small positive examples and a large unlabeled examples can be used. Like Biased-SVM, NPSVM treats the unlabeled set as the negative set with noise, while NPSVM is modified so that, the first primal problem is constructed such that all the...
Recently with the rapid developing of economy, the problem of seawater eutrophication due to pollution of marine environment becomes more serious. Seawater eutrophication will lead to more reproduction of algae in seawater, the reproduction state of algae can be obtained by monitoring the concentration of seawater chlorophyll-a. A soft sensing method of measuring the concentration of seawater chlorophyll-a...
Video caption extraction has become a very popular research area in the last few decades. Many reasons makes it a challenging task. A large number of techniques have been proposed to address this problem. This paper reviews the progress in this area and various methods towards different stages of text extraction in videos, and also discusses the promising direction of the future research.
Aspect-Oriented Programming (AOP) is a new programming paradigm. It is a further development of process oriented, object-oriented method. By introducing the concept of “Aspect”, AOP makes the separation of concerns better, decreases code tangling, solves problems of cross cutting concerns and improves the software quality and efficiency. This paper discusses adding aspect-oriented language facilities...
The support vector machine is a powerful supervised learning algorithm that has been successfully applied to a plenty of fields including text and image recognition, medical diagnosis and so on. The kernel and its parameters optimization, formally known as model selection, is a crucial factor which influences a good tradeoff between bias and variance. To automate model selection of support vector...
In apple harvesting robot stereo vision system, fruit recognition based on least squares support vector machine (LS-SVM) and calibration based on binocular vision are proposed, in order to gain the location information of apples including depth. Firstly, vector median filtering, opening and closing operations are employed, then feature vectors, H and S components in HIS color model and shape features,...
In object matching and recognition it is useful to represent an image with the sets of local features such as SIFT etc. However this representation poses a challenge to the popular SVM machine learning method, since it needs ordered and fixlength data. To solve this problem, we focus in this paper on a Max-matching context kernel, which computes Max-matching points based on the angle between two points...
Scope: Commercial banks, as the key of the nation's economy and the center of financial credit, play a multiple irreplaceable role in the financial system. Credit risks threaten the economic system as a whole. Therefore, predicting bank financial credit risks is crucial to prevent and lessen the incoming negative effects on the economic system. Objective: This study aims to apply a credit risk assessment...
In the robot vision system of the apple harvesting robot, the key is to recognize and locate the apple. To solve recognition questions such as high error rate, too much calculation and time consuming, a new recognizing method, support vector machine (SVM) is applied to improve recognition accuracy and efficiency. At first, vector median filter is used to remove the color images noise of apple fruit...
To improve the learning and generalization ability of the machine-learning model, a new compound kernel that may pay attention to the similar degree between sample space and feature space is proposed. In this paper, used the new compound kernel support vector machine to a speech recognition system for Chinese isolated words, non-specific person and middle glossary quantity, and compared the speech...
We describe two approaches to reducing human fatigue in interactive evolutionary computation (IEC). A predictor function is used to estimate the human user's score, thus reducing the amount of effort required by the human user during the evolution process. The fuzzy system and four machine learning classifier algorithms are presented. Their performance in a real-world application, the IEC-based design...
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