The proceedings contain 106 papers. The topics discussed include: improving video-based IRIS recognition via local quality weighted super resolution;keystroke authentication on mobile devices with a capacitive display...
ISBN:
(纸本)9789898565419
The proceedings contain 106 papers. The topics discussed include: improving video-based IRIS recognition via local quality weighted super resolution;keystroke authentication on mobile devices with a capacitive display;optimal Bayes classification of high dimensional data in face recognition;distance-based algorithm for biometric applications in meanwaves of subject's heartbeats;Bayesian regularized committee of extreme learning machine;latent ambiguity in latent semantic analysis?;automatic update and completion of occluded regions for accurate 3D urban cartography by combining multiple views and multiple passages;a flexible particle swarm optimization based on global best and global worst information;on the strategy to follow for skeleton pruning;recognition of untrustworthy face images in ATM sessions using a bio-inspired intelligent network;and a search engine for retrieval and inspection of events with 48 human actions in realistic videos.
This paper introduces a novel Pythagorean fuzzy patternrecognition-(PFPR) model for the evaluation of the Social Inclusion Index (SII) in Azerbaijan, a crucial component of the Social Quality framework. The approach ...
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ISBN:
(纸本)9783031734168;9783031734175
This paper introduces a novel Pythagorean fuzzy patternrecognition-(PFPR) model for the evaluation of the Social Inclusion Index (SII) in Azerbaijan, a crucial component of the Social Quality framework. The approach takes into account the fuzziness of input data and the fuzziness generated throughout the computation process, utilizing Pythagorean fuzzy (PF) logic tools. The proposed model integrates operations framing the PFPR process. Compared to existing multiple-criteria decision-making methods, the contemplated algorithm enhances the computation of socio-economic indices. The paper explores the multidimensional nature of social inclusion, emphasizing its role in creating equal opportunities and facilitating engagement across various societal spheres. To measure social inclusion, the study addresses challenges related to defining social inclusion and identifying indicators, drawing on approaches from institutions such as the European Commission and Eurostat. The results obtained reveal the SII level in Azerbaijan, and the proposed approach demonstrates its applicability in analyzing and estimating various socio-economic phenomena.
Discriminative nonlinear dimensionality reduction aims at a visualization of a given set of data such that the information contained in the data points which is of particular relevance for a given class labeling is di...
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ISBN:
(纸本)9789898565419
Discriminative nonlinear dimensionality reduction aims at a visualization of a given set of data such that the information contained in the data points which is of particular relevance for a given class labeling is displayed. We link this task to an integration of the Fisher information, and we discuss its difference from supervised classification. We present two potential application areas: speed-up of unsupervised nonlinear visualization by integration of prior knowledge, and visualization of a given classifier such as an SVM in low dimensions.
This paper applies two-dimensional conditional random fields (2D CRF) to page analysis and information extraction. In this paper we discuss features and labels for information extraction by 2D CRF. We evaluated the me...
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ISBN:
(纸本)9789898565419
This paper applies two-dimensional conditional random fields (2D CRF) to page analysis and information extraction. In this paper we discuss features and labels for information extraction by 2D CRF. We evaluated the method by applying it to the problem of extracting bibliographic components from scanned title pages of academic papers. The experimental results show that 2D CRF improves the performance of information extraction compared to chain-model CRF.
Shape analysis has been an area of interest and research in image processing for a long time. Developing a discriminant shape representation and description method is a concern in many applications like image retrieva...
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ISBN:
(纸本)9789898565419
Shape analysis has been an area of interest and research in image processing for a long time. Developing a discriminant shape representation and description method is a concern in many applications like image retrieval systems. This paper presents a new shape representation model which is based on graphs. We also present developed similarity measure technique to find correspondences between shapes. In our approach, features extracted from boundary of the shape are used to build up a graph. By means of a novel solution for attributed graph matching a new method for shape similarity measure is built up.
In this paper we propose two novel rotation invariant local texture descriptors. They are based on Local Binary pattern (LBP), which is one of the most effective and frequently used texture descriptor. Although LBP ef...
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ISBN:
(纸本)9789898565419
In this paper we propose two novel rotation invariant local texture descriptors. They are based on Local Binary pattern (LBP), which is one of the most effective and frequently used texture descriptor. Although LBP efficiently captures the local structure, it is not rotation invariant. In the proposed methods, a dominant direction is evaluated in a circular neighbourhood and the descriptor is computed with respect to it. The weights associated with the neighbouring pixels are circularly shifted with respect to this dominant direction. Further, in the second descriptor, the uniformity of the patterns is utilized to extract more discriminative information. The proposed methods are tested for the task of texture classification and the performance is compared with original LBP and its existed extensions.
In this paper we present a new content-based retrieval descriptor, density-based silhouette descriptor (DBS). It characterizes a 3D object with multivariate probability functions of its 2D silhouette features. The new...
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ISBN:
(纸本)9789898565419
In this paper we present a new content-based retrieval descriptor, density-based silhouette descriptor (DBS). It characterizes a 3D object with multivariate probability functions of its 2D silhouette features. The new descriptor is computationally efficient and induces a permutation property that guarantees invariance at the matching stage. Also, it is insensitive to small shape perturbations and mesh resolution. The retrieval performance on several 3D databases shows that the DBS provides state-of-art discrimination over a broad and heterogeneous set of shape categories.
Presented paper is focused on fast near surface anomaly detection in potential data. Our aim is to find fast and semi-automated anomaly detection technique for the near surface anomalies with defined geometry. The pro...
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ISBN:
(纸本)9789898565419
Presented paper is focused on fast near surface anomaly detection in potential data. Our aim is to find fast and semi-automated anomaly detection technique for the near surface anomalies with defined geometry. The proposed algorithm is based on the shape recognition. The edge and line detection is used on acquired data to detect the typical shape of the anomaly. Shape geometry parameters are converted into the anomaly parameters and location information. The technique was tested using a set of noise-free and noisy synthetic gravity data;satisfactory results were obtained.
We propose a novel gesture spotting approach that offers a comprehensible representation of automatically inferred spatiotemporal constraints. These constraints can be defined between a number of characteristic contro...
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ISBN:
(纸本)9789898565419
We propose a novel gesture spotting approach that offers a comprehensible representation of automatically inferred spatiotemporal constraints. These constraints can be defined between a number of characteristic control points which are automatically inferred from a single gesture sample. In contrast to existing solutions which are limited in time, our gesture spotting approach offers automated reasoning over a complete motion trajectory. Last but not least, we offer gesture developers full control over the gesture spotting task and enable them to refine the spotting process without major programming efforts.
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