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The thematic information extraction has been a difficult problem in high-resolution remote sensing application. Principal component analysis (PCA) is able to extract data's independent features on the basis of the second-order statistics, the variational Bayesian independent component analysis (VBICA) not only overcome the inconsistency between the standard ICA model and remote sensing image but also...
In High Efficiency Video Coding (HEVC), optimal coding unit (CU) size is decided based on recursive rate-distortion cost comparison, which consumes high computational resources. In this paper, an effective HEVC intra CU size decision algorithm is proposed to speed up the encoding process. The algorithm is based on progressive Bayesian classification, which is composed of two cascade classifiers: a...
Short message is one of the most common communication media for mobile subscribers, so major mobile operators are devoted to improve their Short Message Service (SMS). However, the annoying and undesired messages, also named message spam or simply spam, not only worsen the users' experience, but also cause their complaints on SMS. In this paper, we present a novel Chinese SMS spam filtering framework...
Recently, due to the global competition companies active in different industries started to be concerned about the customer churn. With a churn rate of 30%, the telecommunications sector takes the first place on the list. The telecommunications operators need to identify customers who are at risk of churning by implementing predictive models. In this paper, we present an advanced data mining methodology...
WiFi localization problem is basically a multi-sensor data fusion. This paper investigates the use of Bayesian and non-Bayesian Dempster Shafer (DS) data fusion in the context of WiFi-based indoor positioning via fingerprinting. Two novel DS mass choices are discussed. The positioning results are based on real-field measurement data from nine distinct multi-floor buildings in two countries. It is...
Generative Bayesian models have exhibited good performance on the face verification problem, i.e., determining whether two faces are from the same person. As one of the most representative methods, the Joint Bayesian (JB) model represents two faces jointly by introducing some appropriate priors, providing better separability between different face classes. The EM-like learning algorithm of the JB...
Computer aided diagnosis of diseases is less costly, time saving, accurate and it eliminates the need of extra manpower in medical decision making. Many of the surveys related to nutrition reveal that almost quarter of the world's population is anemic. Hence there is an earnest need to develop an efficient machine learning classifier that can detect and classify anemia accurately. In this paper five...
Inspired by the hierarchical cognitive architecture and the perception-action model (PAM) [14], we propose that the internal status acts as a kind of common-coding representation which affects, mediates and even regulates the sensorimotor behaviours. These regulation can be depicted in the Bayesian framework, that is why cognitive agents are able to generate behaviours with subtle differences according...
Sleep apnea-hypopnea syndrome (SAHS) is a chronic sleep-related breathing disorder, which is currently considered a major health problem. In-lab nocturnal polysomnography (NPSG) is the gold standard diagnostic technique though it is complex and relatively unavailable. On the other hand, the analysis of blood oxygen saturation (SpO2) from nocturnal pulse oximetry (NPO) is a simple, noninvasive, highly...
In this paper, we discuss Data Mining and its application in Higher Secondary Directorate of Kerala. Data Mining process has a set of functionalities among which classification has wide application in real world data processing. We examine the Naïve Bayes classification techniques. In the third section, we explain Naïve Bayes Theorem using an experiment. This experiment covers attributes like School...
Anomalous payloads in network packets are a potential source for intrusion in computer networks. In this paper we come up with an efficient machine learning approach to detect anomalous payloads. The approach uses n-gram preprocessing to extract words included in the payload. Bayesian inference is used to learn normal and anomalous traffic patterns from the words extracted during training. During...
In this paper, we present an algorithm for unconstrained face verification based on deep convolutional features and evaluate it on the newly released IARPA Janus Benchmark A (IJB-A) dataset as well as on the traditional Labeled Face in the Wild (LFW) dataset. The IJB-A dataset includes real-world unconstrained faces from 500 subjects with full pose and illumination variations which are much harder...
Email is a rapid and cheap communication medium for sending and receiving information where spam is becoming a nuisance for such communication. A good spam filtering cannot only be achieved by high performance accuracy but low false positive is also necessary. This paper presents a combining classifiers approach with committee selection mechanism where the main objective is to combine individual decisions...
Review of an object or product is important to public judgment of the product. Review can be used in film industry to consider a movie is worth to watch or not. Sentiment classification is used to detect the class of a commentary or review. The purpose of this research is to classify film reviews from Rotten Tomatoes using text mining methods. Classification methods are various like Naive Bayes, Instance...
If the training sample size is asymptotic (number approaching to infinity) classification accuracy for Logistic Regression is often better than the asymptotic accuracy of GNB. Also if the training sample size is scarce, classification accuracy for GNB is often better than the asymptotic accuracy of Logistic Regression. This article shows that, although the Bayesian classifier's probability estimates...
Dempster-Shafer theory is a very powerful tool for data fusion, which provides a good estimation of imprecision, conflict from different sources and deal with any unions of hypotheses. In this paper, we propose to develop a high-performance hybrid Network Intrusion Detection System, based on belief functions. This system contains three levels, the first one includes two fast classifiers: Naïve Bayes...
Degradation data is an important information source which is usually used to predict products' lifetime, for instance in accelerated degradation testing (ADT) and health management. Degradation data can be easier and cheaper obtained than failure data. As a result, it has been widely applied. However, due to some restrictions of funds and the development cycle, the degradation data of some products...
The disease Leukemia are continuously increasing among the people. The cause of leukemia is unknown but several factors, however are associated with the development of leukemia that are exposure to ionising radiation, exposure to benzene in rubber industry workers, cytotoxic drug particularly alkylating agent exposure, genetic disorder like down syndrome and immunological deficiency states. There...
Aiding design and test optimization of analog circuits requires accurate models that can reliably capture complex dependencies of circuit performances on essential circuit and device parameters, and test signatures. We present a novel Bayesian learning technique, namely relevance vector and feature machine (RVFM), for characterizing analog circuits with sparse statistical regression models. RVFM not...
Effective layout pattern sampling is a fundamental component for lithography process optimization, hotspot detection, and model calibration. Existing pattern sampling algorithms rely on either vector quantization or heuristic approaches. However, it is difficult to manage these methods due to the heavy demands of prior knowledges, such as highdimensional layout features and manually tuned hypothetical...
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