This paper presents a novel algorithm for robust object tracking based on the particle filtering method employed in recursive Bayesian estimation and image segmentation and optimisation techniques employed in active contour ...
Ability to recognize human activities will enhance the capabilities of a robot that interacts with humans. However automatic detection of human activities could be challenging due to the individual nature of the activities. ...
The conventional histogram intersection (HI) algorithm computes the intersected section of the corresponding color histograms in order to measure the matching rate between two color images. Since this algorithm is strictly ...
Missing data imputation is an actual and challenging issue in machine learning and data mining. This is because missing values in a dataset can generate bias that affects the quality of the learned patterns or the ...
ABSTRACT: Computing academics report bimodal grade distributions in their CS1 classes. Some academics believe that such a distribution is due to their being an innate talent for programming, a geek gene, which some students ...
Subspace selection is a powerful tool in data mining. An important subspace method is the FisherâRao linear discriminant analysis (LDA), which has been successfully applied in many fields such as biometrics, bioinformatics, ...
Entanglement-assisted quantum error-correcting codes (EAQECCs) make use of pre-existing entanglement between the sender and receiver to boost the rate of transmission. It is possible to construct an EAQECC from any classical ...
In this paper, we study the generalization bound for an empirical process of samples independently drawn from an infinitely divisible (ID) distribution, which is termed as the ID empirical process. In particular, based on ...
Many existing results on statistical learning theory are based on the assumption that samples are independently and identically distributed (i.i.d.). However, the assumption of i.i.d. samples is not suitable for practical ...
Semi-supervised ranking is a relatively new and important learning problem inspired by many applications. We propose a novel graph-based regularized algorithm which learns the ranking function in the semi-supervised learning ...
To solve the problem that the existing algorithms of mining association rules result in a number of rules, upper closed set of an item set and generalized association rule base were defined. And some important propositions ...
Recent-biased approximations have received increased attention recently as a mechanism for learning trend patterns from time series or data streams. They have shown promise for clustering time series and incrementally ...
Local Binary Pattern (LBP) has been well recognised and widely used in various texture analysis applications of computer vision and image processing. It integrates properties of texture structural and statistical texture ...
According to their value ranges, L-topological spaces form different categories. Clearly, the investigation on their relationships is certainly important and necessary. Lowen was one of the first authors who had studied ...
Shannon, AG; Atanassov, K; Riecan, B; Krawczak, M; Orozova, D; Melo-Pinto, P; Sotirova, E; Parvathi, R; Kim, T(IEEE, 2012-01)
A generalized net model of the process of selection and usage of an intelligent e-learning system is constructed. An evaluation of the results of the learning is done. This work is a follow up of previous authors' research ...
The Region Connection Calculus (RCC) is one of the most widely referenced system of high-level (qualitative) spatial reasoning. RCC assumes a continuous representation of space. This contrasts sharply with the fact that ...
On the basis of a new topological minimax theorem, a simple and unified approach is developed to Lagrange duality in nonconvex quadratic programming. Diverse generalizations as well as equivalent forms of the S-Lemma, ...
Aslanzadeh, S; Chaczko, ZC(Foundation of Computer Science, 2013-01)
In Cloud Computing, designing an efficient workflow scheduling algorithm is considered as a main goal. Load balancing is one of the most sophisticated methodologies, which can optimize workflow scheduling by distributing ...
With the emergence of location-aware mobile device technologies, communication technologies and GPS systems, various location-aware queries have attracted great attentions in the database literature. In many user recommendation ...