This paper introduces a new approach of approximating the selectivity of multimedia range queries. Estimating the selectivity of a range query is a pre-requisite to optimize a mul...
In this paper, we propose a novel technique for modelbased recognition of complex object motion trajectories using Hidden Markov Models (HMM). We build our models on Principal Com...
Faisal I. Bashir, Wei Qu, Ashfaq A. Khokhar, Dan S...
— Decision rules generated from reducts can fully describe a data set. We introduce a new method of evaluating rules by taking advantage of rough sets theory. We consider rules g...
High-throughput methods for detecting protein-protein interactions (PPI) have given researchers an initial global picture of protein interactions on a genomic scale. The usefulnes...
In this paper we present our approach to 3D surface reconstruction from large sparse range data sets. In space robotics constructing an accurate model of the environment is very i...
Sebastien Gemme, Joseph Nsasi Bakambu, Ioannis M. ...
We present an adaptive filtering based methodology for resampling 3-D time series images using an extension of the method presented by Westin in [11]. We simultaneously reduce th...
The data mining inspired problem of finding the critical, and most useful features to be used to classify a data set, and construct rules to predict the class of future examples ...
Pablo Moscato, Luke Mathieson, Alexandre Mendes, R...
The identification of near-duplicate keyframe (NDK) pairs is a useful task for a variety of applications such as news story threading and content-based video search. In this pape...
The effective grouping, or partitioning, of semistructured data is of fundamental importance when providing support for queries. Partitions allow items within the data set that sh...
John N. Wilson, Richard Gourlay, Robert Japp, Math...
Visual data mining has been established to effectively analyze large, complex numerical data sets. Especially, the extraction and visualization of inherent structures such as hie...