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To train and evaluate various face recognition algorithms, quite many databases have been created. But most of them have been created under controlled conditions to study the specific variations of the face recognition problem. These variations include position, pose, lighting, background, camera quality and gender. But in real environment, there are also many applications in which there is little...
Schema matching is widely used in many database applications, such as, data integration, data warehouse, data spaces, and ontology merging. In this paper, we propose multi-schema matching based on web structured information sources. There are two meanings at this point. Traditional matching techniques mainly address matching tasks between two attributes, namely pair wise-attribute correspondence....
Virtual machine (VM) consolidation in Cloud computing environments provides a great opportunity for energy saving. However, the obligation of providing suitable quality of service to end users leads to the necessity in dealing with energy-performance tradeoff. In this paper, we propose a redesigned energy-aware heuristic framework for VM consolidation to achieve a better energy-performance tradeoff...
Authors investigate the continuous multi-facility location problems with special metrics including the lift metric and French Metro metric An approach to solving them by using their decomposition into series of simpler problems with the rectilinear (Manhattan, l1) metric is proposed. Well-known procedure, proposed by V. Trubin, is used for solving the problems with the rectilinear metric. Authors...
This paper presents an improved bag-of-words (BoW) framework for detecting near-duplicates of images on the Web and makes three main contributions. Firstly, based on the SIFT feature descriptors, Locality-constrained Linear Coding (LLC) with the spatial pyramid is introduced to encode features. Secondly, a weighted Chi-square distance metric is proposed to compare two histograms, with an inverted...
In this paper we discuss the convergence of the Broyden algorithms without convexity and exact line search assumptions. We proved that if the objective function is suitably smooth and the algorithm produces a convergence point sequence, then the limit point of the sequence is a critical point of the objective function.
The application of key performance indicators (KPIs) in organizational performance measurement (PM) aims to develop and improve targeted objectives. This will include factors of greatest significance to the organization, yet such targeted objectives are not always achieved due to some prevalence of certain problematic issue. This happens on average because the targeted objectives require high productivity...
This paper proposes a new image smoothing method invariant to affine transformation. In the field of image processing and recognition, Gaussian filtering is a common procedure for image smoothing. However Gaussian filtering is not affine invariant. This paper proposes a new method for image smoothing that is invariant under such affine transformation that does not change the area of any region in...
This paper presents a new full-reference image quality measure using discrete orthogonal moments. The sign of the moment is considered and the relative difference of the moments is obtained by comparing the absolute moment difference (AMD) with the magnitude of the original moment. A new quality function is proposed, which is an exponential function of the relative moment difference (RMD). Simulation...
Blur metrics have been used in broad range of applications to quantify the amount of blur especially in images. The spatially varying blur due to defocus or camera shake is hard to estimate. It is observed that the existing blur metrics does not perform well for images having very few or many features. In this work, we present contrast based blur invariant features named as CBIF, which utilizes useful...
Selecting points using min-max strategy can guarantee uniformity of Pareto. But shortcomings are missing effective solutions and poor solutions being selected. By the analysis of choosing points with the min-max strategy and reasonable fitness metric, we propose a new evolutionary method choosing weights on points (point-to-weight). A large number of multi-objective optimization functions have been...
Functional magnetic resonance imaging (fMRI) produces data about activity inside the brain, from which spatial maps can be extracted by independent component analysis (ICA). In datasets, there are n spatial maps that contain p voxels. The number of voxels is very high compared to the number of analyzed spatial maps. Clustering of the spatial maps is usually based on correlation matrices. This usually...
To support the whole business process compliance lifecycle, one also needs to monitor the actual processes and not just check their design. Recently, many approaches have been proposed that utilize a broad range of constraint languages and techniques to realize compliance monitoring solutions. Due to this diversity, the comparison of existing approaches is difficult and consequently hampers the evaluation...
We propose a new metric for effectively and accurately evaluating the performance of self-stabilizing algorithms. Self-stabilization is a versatile category of fault-tolerance that guarantees system recovery to normal behavior within a finite number of steps, when the state of the system is perturbed by transient faults (or equally, the initial state of the system can be some arbitrary state). The...
The new format of the didactic systems for the organization of the training of engineers are considered. These systems are focused on the rapid development of the technical intelligence of the student. In practice, they have shown the high efficiency.
This work delves into variations of FSS that uses local information (i.e. fish weights) for splitting the school and presents comparative analyses of the new method, tried here in three ways. Hence, this is an attempt to create a more economical alternative for the best performing multimodal version of the algorithm FSS, the dFSS. The work capitalizes on some modifications in the Collective Instinctive...
Table understanding is a well studied problem in document analysis, and many academic and commercial approaches have been developed to recognize tables in several document formats, including plain text, scanned page images and born-digital, object-based formats such as PDF. Despite the abundance of these techniques, an objective comparison of their performance is still missing. The Table Competition...
Nowadays, many software projects are partially or completely open-source based. There is an increasing need for companies to participate in open-source software (OSS) projects, e.g., in order to benefit from open source ecosystems. OSS projects introduce particular challenges that have to be understood in order to gain the benefits. One such challenge is getting newcomers onboard into the projects...
This paper presents the results of the Handwriting Segmentation Contest that was organized in the context of the ICDAR2013. The general objective of the contest was to use well established evaluation practices and procedures to record recent advances in off-line handwriting segmentation. Two benchmarking datasets, one for text line and one for word segmentation, were created in order to test and compare...
In this paper, we present an automatic marking system for marking interactive exercises related to heuristic search algorithms. It aims to assist tutors in assessing the performance of students and reduce the workload associated with their marking task. Also, it provides individualized and immediate feedback to the students. Automatic marking is achieved in two stages. First, the system compares a...
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