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In the recent years, forests of decision trees have seen an increasing interest from the Machine Learning community since they allow to aggregate the decisions from a set of decision trees into one robust answer. However, this approach suffers from two well-known limits: first, their performances depend on the number of trees and thus finding the right size and how to aggregate decisions could be...
Objects are usually described by combinations of properties. Logic-based descriptions offer compact representations for binary properties. Besides, Sugeno integrals are well-known as a powerful qualitative aggregation tool in multiple-criteria decision, which is applicable to gradual properties, and takes into account positive synergies between properties. The paper proposes to investigate the potential...
Supervised classification has been extensively addressed in the literature as it has many applications, especially for text categorization or web content mining where data are organized through a hierarchy. On the other hand, the automatic analysis of brand names can be viewed as a special case of text management, although such names are very different from classical data. They are indeed often neologisms,...
This paper presents an iris recognition method based on the two dimensional dual-tree complex wavelet transform (2D-CWT) and the support vector machines (SVM). 2D-CWT has such significant properties as the approximate shift-invariance, high directional selectivity and computationally much more efficient. These properties are very useful in invariant iris recognition. SVM is used as a classifier and...
In this paper we describe a methodology and an automatic procedure for inferring accurate and easily understandable expert-system-like rules from forensic data. This methodology is based on the fuzzy set theory. The algorithms we used are described in detail, and were tested on forensic data sets. We also present in detail some examples, which are representative for the obtained results.
Jaundice is the most common condition that requires medical attention in newborns. Although most newborns develop some degree of jaundice, a high level bilirubin puts a newborn at risk of bilirubin encephalopathy and kernicterus which are rare but still occur in Egypt. In this paper, a new weighted rough set framework is introduced for early intervention and prevention of neurological dysfunction...
In this paper we present our results of fingertip detection to realize an automatic gesture recognition system by using a multi stereo camera setup. The online framework detects automatically the hands and the face of the user based on depth and color information. To estimate the spatial position and the joints of fingers a 3D hand model was generated. We used the Iterative Closest Point (ICP) algorithm...
The paper considers automatic visual recognition of signed expressions. The proposed method is based on modeling gestures with subunits, which is similar to modeling speech by means of phonemes. To define the subunits a data-driven procedure is applied. The procedure consists in partitioning time series, extracted from video, into subsequences which form homogeneous groups. The cut points are determined...
This paper proposes a novel approach for determining the integration criteria using Particle filter for fusion of hand gesture and posture recognition system at decision level. For decision level fusion, integration framework requires the classification of hand gesture and posture symbols in which HMM and SVM are used to classify the alphabets and numbers from gesture and posture recognition system...
There are close links between mathematical morphology and rough set theory. Both theories are successfully applied among others to image processing and pattern recognition. This paper presents a new generalization of the classical rough set theory, called the partial approximative set theory (PAST). According to Pawlak's classic rough set theory, the vagueness of a subset of a finite universe is defined...
We propose a possibility theory-based approach to the treatment of missing user preferences in skyline queries. To compensate this lack of knowledge, we show how a set of plausible preferences suitable for the current context can be derived either in a case-based reasoning manner, or using an extended possibilistic logic setting. Uncertain dominance relationships are defined in a possibilistic way...
In this paper, we consider relational databases containing uncertain attribute values, in the situation where some knowledge is available about the more or less certain value (or disjunction of values) that a given attribute in a tuple can take. We propose a possibility-theory-based model suited to this context and extend the operators of relational algebra in order to handle such relations in a “compact”...
Real-time feature extraction is a key component for any action recognition system that claims to be truly real-time. In this paper we present a conceptually simple and computationally efficient method for real-time human activity recognition based on simple statistical features. Such features are very cheap to compute and form a relatively low dimensional feature space in which classification can...
Correlating estimates of objective measures related to the presence of different coding artifacts with the quality of video as perceived by human observers is a non-trivial task. There is no shortage of data to learn from, thanks to the Internet and web-sites such as YouTubetm. There has, however, been little done in the research community to try to use such resources to advance our understanding...
The governing behaviors of individuals in crowded places offer unique and difficult challenges, and limit the scope of conventional surveillance systems. In this paper, we investigate the crowd behaviors and localize the anomalies due to individual's abrupt dissipation. The novelty of the proposed approach can be described in three aspects. First, we introduce block-clips by sectioning the video segments...
A novel fingerprint indexing scheme for embedded system is presented in this paper. Our approach is a model-based one, which efficiently retrieves correct hypotheses using novel rotation-invariant features formed by the core and minutiae of fingerprint image. Differently from most existing fingerprint indexing approaches, the proposed algorithm is suitable for embedded systems because it is not time...
Recognition by Indexing and Sequencing (RISq) is a general-purpose method for classification of temporal vector sequences. We developed an advanced version of RISq and applied it to isolated-word speech recognition, a task most commonly performed with Hidden Markov Models (HMMs) or Dynamic Time Warping (DTW). RISq is substantially different from both these methods and presents several advantages over...
Iris recognition has been recently given greater attention in human identification and it's becoming increasingly an active topic in research. This paper presents a personal identification method based on iris. The Method includes three steps. In the first one, the eye image is processed in order to obtain a segmented and normalized eye image by applying an integrodifferential operator, Hough transform...
The field of Text Mining has evolved over the past years to analyze textual resources. However, it can be used in several other applications. In this research, we are particularly interested in performing text mining techniques on audio materials after translating them into texts in order to detect the speakers' emotions. We describe our overall methodology and present our experimental results. In...
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