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The paper proposed a novel method for lip recognition based on Active Basis Model (ABM). There are four stages in a flowchart of this novel method. At the first stage the deformable templates of lip images is obtained. The lip images of deformable templates are obvious open or closed. The second stage is to obtain the deformed template of each testing images. The third stage, the difference between...
Air temperature is closely related to life and affects all aspects of life. Therefore, the forecast of the temperature is more far-reaching. In this paper, a new model based on EMD (Empirical Mode Decomposition) and LS-SVM (Least Squares Support Vector Machine) was proposed. At first, EMD was applied to adaptively decomposing the time series into a series of different scales of intrinsic mode function...
Coreference is a common linguistic phenomenon in natural language understanding, it plays an important role in simplifying the expression and linking up the context. In this paper, the algorithm of support vector machines is applied to solve the problem of Chinese coreference, we consider fully the important characteristics which related to coreference and integrate them effectively to build model...
This paper proposes an unsupervised speaker clustering system for duration of speech signals below 4 seconds. For determining whether two collected speech sections uttered from the same speaker or not, our previous SVM training miss-classification rate (STMR) is adopted to evaluate the data separability between two different speakers. This paper also proposes a hierarchical extract and merge (HEM)...
Most existing semi-supervised methods implemented either the cluster assumption or the manifold assumption. The performance will degrade if the assumption was not proper for the data. A method was proposed by combining both the cluster assumption and the manifold assumption. A semi-supervised kernel which reflected geometric information of the samples was constructed through warping the Reproducing...
In Computer Vision, problem of identifying or classifying the objects present in an image is called Object Categorization. It is challenging problem, especially when the images have clutter background, occlusions or different lighting conditions. Many vision features have been proposed which aid object categorization even in such adverse conditions. Past research has shown that, employing multiple...
In view of the corrosion of cooling water system, the dynamic simulation test was conducted with the cooling water dynamic simulation experiment device. In the test period the corrosion rate and the water quality factors were monitored. Based on the test data, an intelligent prediction model of cooling water corrosion rate based on least squares support vector machine (LS-SVM) is constructed, in which...
This paper presents a systematic design of an efficient cloud framework for wellness self-management devices and services. The innovative wellness self-management devices and services performs the following functions: (1) Collecting GPS, accelerometer, temperature, image data and personal profiles, (2) Fusing data and recognizing the state, (3) Performing predictive constantly analytics on the sequence...
For last few years, researchers are increasingly employing machine learning methods in the domain of cancer prognosis. The main reason behind these efforts is to help oncologist to make accurate and less invasive decisions for the patient's treatment. Moreover, it would relieve many cancer patients from agonizingly complex surgical treatments and their colossal costs. In this paper, we have proposed...
Designing and developing automatic techniques for magnetic resonance images (MR) for data analysis is very challenging. One popular and public available method, FAST (FMRIB Automatic Segmentation Tool) has been widely used for automatic brain tissue segmentation for this purpose. This paper investigates limitations of this software algorithm on implementation and further develops a new approach to...
Five different classification models, namely RFR_SUM, CRFs, Maximum Entropy, SVM and Semantic Similarity Model, are employed for polyphonic disambiguation. Based on observation of the experiment outcome of these models, an additional ensemble method based on majority voting is proposed. The ensemble method obtains an average precision of 96.78%, which is much better than the results obtained in previous...
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