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Writer identification is a classification problem where the classes correspond to a group of writers and the data points are their handwriting samples. This paper proposes an approach to offline text-sensitive writer identification on the basis of a probabilistic generative model of isolated handwritten digits. The model parameters are learned separately for each writer, and the writer of query samples...
Since Web 2.0 emerges, users became very active in attending Web forum and Q&A Community. For the community about technology, engineering and science, it is likely that most of the professionals follow the same general path to study specific knowledge and this path would be between topics from basic one to specific one or from topic about old technology to a topic about new technology. Our work...
Bayesian network (BN), an important machine learning technique, has been widely used in modeling relationships among random variables. BN is considered to be suitable for tasks like prediction, classification and cause analysis. In fact, Bayesian network model often preforms better precision than other commonly used algorithm models in classification and prediction. Meanwhile, taking Max-Min-Hill-Climbing...
Exploiting both labeled and unlabeled instances of various problems seems a really promising strategy, since useful information that is contained on the latter pool of data is discarded during supervised approaches. However, the size of the unlabeled data that needs to be examined is usually extremely large and efficient algorithms should be utilized in such cases. Hidden Naive Bayes (HNB) model constitutes...
Bayesian network (BN) classifiers with powerful reasoning capabilities have been increasingly utilized to detect intrusion with reasonable accuracy and efficiency. However, existing BN classifiers for intrusion detection suffer two problems. First, such BN classifiers are often trained from data using heuristic methods that usually select suboptimal models. Second, the classifiers are trained using...
This paper elaborates the basic structure of a machine learning system in classifying affective state. There are several techniques in classifying the states depending on the type of input-output dataset. A proper selection of techniques is crucial in determining the success rate of the system prediction. The paper proposes a machine learning technique in classifying affective states of human subjects...
Along with the improvement of equipment reliability, human error has become a great threat to the power system reliability and safety. However, the research of human reliability analysis in power system is still in its infancy. There is still little approach for quantitatively measuring the human reliability of power system. In this paper, the definition of human reliability of power system and a...
Malicious users of the internet can launch Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks with the intent of making the throughput of a network next to none. As the types and number of users of the internet increases, the requirement of an effective Intrusion Detection System(IDS) to detect these attacks also increases. Different techniques such as data mining and pattern...
In computer vision, semantically accurate segmentation of an object is considered to be a critical problem. The different looking fragments of the same object impose the main challenge of producing a good segmentation. This leads to consider the high-level semantics of an image as well as the low-level visual features which require computationally intensive operations. This demands to optimize the...
In this paper a new islanding detection technique for grid-mode distributed-generation (DG) is proposed. Twenty one features are extracted from measurement of the voltage and frequency at the point of common coupling (PCC) in order to identify islanding occurrence with high accuracy. An IEEE 34-bus system was used in this paper to generate islanding and non-islanding training cases. Then a Support...
Situation awareness of operators plays a key role in the safety of a nuclear power plant. The establishment of a situation awareness assessment model (SAAM) is the foundation of an advanced HRA method. The paper firstly ascertains the relation between situation awareness and human reliability analysis and then forms an organization-committed cause-effect conception model. On the basis of the above,...
In order to coordinate with and promote the scientific process of the national fencing team, we developed the decision support system for training. In fencing training, we established a two-way reasoning model based on Bayesian network and found the relationship between training process and physiological indicators. Combined with experienced knowledge and sample data, we did research on knowledge...
In this paper, we propose a feature generation and classification approach for universal steganalysis based on genetic algorithm (GA) and higher order statistics. The GA is utilized to select a subset of candidate features, a subset of candidate transformations to generate new features. The logistic regression model and Bayesian network model are then used as the classifier. Experimental results show...
Building extraction from high resolution Synthetic Aperture Radar (SAR) images can benefit from modelling the interaction of several elements in urban scene. This paper proposes a Bayesian approach to exploit the interplay. The appearances of buildings in SAR images are dependent on their orientation angles. We estimate the orientation angles of buildings by supervised learning. The knowledge of other...
This paper addresses the problem of developing facial image quality metrics that are predictive of the performance of existing biometric matching algorithms and incorporating the quality estimates into the recognition decision process to improve overall performance. The first task we consider is the separation of probe/gallery qualities since the match score depends on both. Given a set of training...
Designing, building, and launching missions to deploy space based sensors typically take many years and cost billions of dollars. Missions are often delayed or canceled, and data from some parts of the world may be unavailable. When a physical sensor is unavailable for any reason, we propose the notion of a virtual sensor, in which we exploit the hundreds of spaced based sensors already observing...
Now the demand for intelligent video processing is getting greater and greater, moving body behavior classification from video images is their focus and difficulty. An approach to extracting human body and classifying the behaviors of the moving objects is presented in this paper. A statistical Gaussian model is used as adaptive background updating method. After foreground objects are segmented from...
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