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Iris recognition is a biometric authentication system proving vital for ensuring security and has been employed as an important case to test the algorithms developed in pattern recognition. The unique circular shape of the iris and its time invariance makes it a versatile technique that has an accuracy that can be mathematically proven. Here in this work we propose a new segmentation technique and...
The concept of indoor location positioning has been around for decades now. Despite the existence of many algorithms that can achieve location positioning with remarkable performance in terms of accuracy, implementation of such algorithms has not been done on a large scale. There is a trade-off between the positioning accuracy and the complexity of the algorithm. This paper introduces and explains...
Cluster Analysis methods are very important, popular data summarization techniques applied in diverse environments. These techniques retrieve the hidden patterns in large datasets in the form of characterized patterns which can be interpreted further in different contexts. Widespread use of medical information systems and explosive growth of medical databases require traditional manual data analysis...
Extensive research has been conducted in an effort to evaluate methods and techniques for image segmentation. However, while most literature has focused on evaluating automatic and semi-automatic algorithms, works evaluating interactive segmentation algorithms are less numerous. Note that interactive segmentation can improve results by adding prior knowledge from users into the process. Although this...
A novel method is introduced for label propagation on similarity tensors. The proposed method operates on data with multiple representations. A higher order similarity matrix is constructed for describing the relationship between the data representations in different modalities. Then, label propagation is performed on the above mentioned similarity matrix, by extending the state of the art label propagation...
The purpose of the presented research was the development of a melody search system that would allow to find a song in a music database, based on humming the tune of a known song fragment. The melody recognition in the developed system is based on comparing vectors of voice pitch values. The best match of the humming pitch vector against all the recordings in the database is searched. An original...
Fast audio retrieval is crucial for many important applications and yet demanding due to the high dimension nature and increasingly larger volume of audios in the internet. Although audio fingerprinting can greatly reduce its dimension while keeping audio identifiable, the dimension of audio fingerprints is still too high to scale up for big audio data. The tradeoff between the accuracy and the efficiency...
Alarm fatigue can cause many negative results. Regarding ECG signals, an algorithm to reduce alarm fatigue is described, regardless of whether or not VPBs are involved in the false alarms. ECG signals are divided into five signal quality index levels (SQI): 0∼4, where level 0 represents a noise free signal and level 4 indicates the worst signal quality. The key of the method is to judge the noise...
Face recognition has achieved immense popularity in various fields because of its robustness and accuracy. But pose variation is still a major obstacle to overcome for effective face recognition in an uncontrolled environment. A wide variety of face recognition algorithms have been proposed in the past. In this paper we exhibit a review of some of the common algorithms that expect to conquer on the...
In the recent years, contour-based shape representation is an important issue in the object recognition research area. In this paper, a new shape descriptor A-DCE is proposed based on DCE and DP for contour deformation and recognition. Firstly, the object contour is evolved adaptively by DCE to extract the contour information with important visual parts. Secondly, the costing feature descriptor is...
In this paper, a single hidden-layer feedforward fusion network is proposed for face identity verification. Essentially, the feature extraction, matching score calculation and fusion algorithm design steps are integrated and absorbed into a hidden layer of the model. Each hidden node works on the raw face image directly and produces an Euclidean distance based match score within the network. These...
Indoor positioning based on Wi-Fi signal attracts a lot of attention in the location field. However, accuracy of positioning is often affected due to the instability of indoor Wi-Fi signal. In order to overcome this problem and reduce the errors, we present a new indoor WiFi-based positioning algorithm called FMA-RRSS which is the abbreviation of Fingerprint Matching Algorithm Based on Relative Received...
Effective machine-learning handles large datasets efficiently. One key feature of handling large data is the use of databases such as MySQL. The freeware fuzzy decision tree induction tool, FDT, is a scalable supervised-classification software tool implementing fuzzy decision trees. It is based on an optimized fuzzy ID3 (FID3) algorithm. FDT 2.0 improves upon FDT 1.0 by bridging the gap between data...
Data stored in educational database is increasing day by day. Data mining algorithms can be used to find hidden patterns from the student's database. These patterns can be used to find academic performance of students. The main aim of this study was to determine factors that influence the student's performance. This paper proposes Generalized Sequential Pattern mining algorithm for finding frequent...
The digital analysis of heart sounds has revealed itself as an evolving field of study. In recent years, numerous approaches to create decision support systems were attempted. This paper proposes two novel algorithms: one for the segmentation of heart sounds into heart cycles and another for detecting heart murmurs. The segmentation algorithm, based on the autocorrelation function to find the periodic...
In this paper, we focus on developing a novel noise-robust LBP-based texture feature extraction scheme for texture classification. Specifically, two solutions have been proposed to overcome the primary two reasons that cause local binary pattern sensitive to noise. First, a hybrid model is proposed for noise-robust texture description. In this new model, the local primitive micro features are encoded...
In this paper, we propose a semi-supervised temporal clustering method and apply it to the complex problem of facial emotion categorization. The proposed method, which uses a mechanism to add side information based on the semi-supervised kernel k-means framework, is an extension of the temporal clustering algorithm Aligned Cluster Analysis (ACA). We show that simply adding a small amount of soft constraints,...
Kernel learning is an important research topic in the machine learning area. Research on self-optimization learning of kernel function and its parameter has an important theoretical value for solving the kernel selection problem widely endured by kernel learning machine, and has the same important practical meaning for the improving of kernel learning systems. In this paper, we focus on two schemes:...
A machine translation is developed to preserve the existence of Javanese speech levels. The machine translation relies on a phrase-based bi-text alignment to form the language corpora. The edit shifting distance is applied to increase the alignment efficiency. However, improper alignment contributed by recorded impossible pair and insufficient data training is still detected. This paper proposes a...
In this paper, we introduce a set of new visual representations for complex systems. These visual representations allow for the efficient description of systems that encapsulate a variety of components that can be merged together to form ensembles. These ensemble methods can outperform individual approaches. The whole operation of such systems can be better interpreted using visual tools. Thus, we...
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