Search results for "Tree"
showing 10 items of 1841 documents
Cholesky decomposition techniques in electronic structure theory
2011
We review recently developed methods to efficiently utilize the Cholesky decomposition technique in electronic structure calculations. The review starts with a brief introduction to the basics of the Cholesky decomposition technique. Subsequently, examples of applications of the technique to ab inito procedures are presented. The technique is demonstrated to be a special type of a resolution-of-identity or density-fitting scheme. This is followed by explicit examples of the Cholesky techniques used in orbital localization, computation of the exchange contribution to the Fock matrix, in MP2, gradient calculations, and so-called method specific Cholesky decomposition. Subsequently, examples o…
A GPU-Based DVC to H.264/AVC Transcoder
2010
Mobile to mobile video conferencing is one of the services that the newest mobile network operators can offer to users With the apparition of the distributed video coding paradigm which moves the majority of complexity from the encoder to the decoder, this offering can be achieved by introducing a transcoder This device has to convert from the distributed video coding paradigm to traditional video coding such as H.264/AVC which is formed by simpler decoders and more complex encoders, and allows to the users to execute only the low complex algorithms In order to deal with this high complex video transcoder, this paper introduces a graphics processing unit based transcoder as base station The…
Learning Improved Feature Rankings through Decremental Input Pruning for Support Vector Based Drug Activity Prediction
2010
The use of certain machine learning and pattern recognition tools for automated pharmacological drug design has been recently introduced. Different families of learning algorithms and Support Vector Machines in particular have been applied to the task of associating observed chemical properties and pharmacological activities to certain kinds of representations of the candidate compounds. The purpose of this work, is to select an appropriate feature ordering from a large set of molecular descriptors usually used in the domain of Drug Activity Characterization. To this end, a new input pruning method is introduced and assessed with respect to commonly used feature ranking algorithms.
A new image segmentation approach using community detection algorithms
2015
Image segmentation has an important role in many image processing applications. Several methods exist for segmenting an image. However, this technique is still a relatively open topic for which various research works are regularly presented. With the recent developments on complex networks theory, image segmentation techniques based on graphs has considerably improved. In this paper, we present a new perspective of image segmentation, by applying three of the most efficient community detection algorithms, Louvain, infomap and stability optimization based on the louvain algorithm, and we extract communities in which the highest modularity feature is achieved. After we show that this measure …
The predictive power of game-related statistics for the final result under the rule changes introduced in the men’s world water polo championship: a …
2019
The objectives of this study were (i) to compare water polo game-related statistics by match outcome (winning and losing teams) after the application of the new rules, and (ii) to develop a classif...
Projection Clustering Unfolding: A New Algorithm for Clustering Individuals or Items in a Preference Matrix
2020
In the framework of preference rankings, the interest can lie in clustering individuals or items in order to reduce the complexity of the preference space for an easier interpretation of collected data. The last years have seen a remarkable flowering of works about the use of decision tree for clustering preference vectors. As a matter of fact, decision trees are useful and intuitive, but they are very unstable: small perturbations bring big changes. This is the reason why it could be necessary to use more stable procedures in order to clustering ranking data. In this work, a Projection Clustering Unfolding (PCU) algorithm for preference data will be proposed in order to extract useful info…
Entropy-Based Classifier Enhancement to Handle Imbalanced Class Problem
2017
The paper presents a possible enhancement of entropy-based classifiers to handle problems, caused by the class imbalance in the original dataset. The proposed method was tested on synthetic data in order to analyse its robustness in the controlled environment with different class proportions. As also the proposed method was tested on the real medical data with imbalanced classes and compared to the original classification algorithm results. The medical field was chosen for testing due to frequent situations with uneven class ratios.
Efficient Multi-scale Patch-Based Segmentation
2015
The objective of this paper is to devise an efficient and accurate patch-based method for image segmentation. The method presented in this paper builds on the work of Wu et al. [14] with the introduction of a compact multi-scale feature representation and heuristics to speed up the process. A smaller patch representation along with hierarchical pruning allowed the inclusion of more prior knowledge, resulting in a more accurate segmentation. We also propose an intuitive way of optimizing the search strategy to find similar voxel, making the method computationally efficient. An additional approach at improving the speed was explored with the integration of our method with Optimised PatchMatch…
From the nearest neighbour rule to decision trees
1998
This paper proposes an algorithm to design a tree-like classifier whose result is equivalent to that achieved by the classical Nearest Neighbour rule. The procedure consists of a particular decomposition of a d-dimensional feature space into a set of convex regions with prototypes from just one class. Some experimental results over synthetic and real databases are provided in order to illustrate the applicability of the method.
A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning
2017
Progress in biomechanical modelling of human soft tissue is the basis for the development of new clinical applications capable of improving the diagnosis and treatment of some diseases (e.g. cancer), as well as the surgical planning and guidance of some interventions. The finite element method (FEM) is one of the most popular techniques used to predict the deformation of the human soft tissue due to its high accuracy. However, FEM has an associated high computational cost, which makes it difficult its integration in real-time computer-aided surgery systems. An alternative for simulating the mechanical behaviour of human organs in real time comes from the use of machine learning (ML) techniq…