Search results for "Computation"
showing 10 items of 7362 documents
Low-Rate Reduced Complexity Image Compression using Directionlets
2006
The standard separable two-dimensional (2-D) wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to capture efficiently one-dimensional (1-D) discontinuities, like edges and contours, that are anisotropic and characterized by geometrical regularity along different directions. In our previous work, we proposed a construction of critically sampled perfect reconstruction anisotropic transform with directional vanishing moments (DVM) imposed in the corresponding basis functions, called directionlets. Here, we show that the computational complexity of our transform is comparable to the co…
A Variational Approach for Denoising Hyperspectral Images Corrupted by Poisson Distributed Noise
2014
Poisson distributed noise, such as photon noise is an important noise source in multi- and hyperspectral images. We propose a variational based denoising approach, that accounts the vectorial structure of a spectral image cube, as well as the poisson distributed noise. For this aim, we extend an approach for monochromatic images, by a regularisation term, that is spectrally and spatially adaptive and preserves edges. In order to take the high computational complexity into account, we derive a Split Bregman optimisation for the proposed model. The results show the advantages of the proposed approach compared to a marginal approach on synthetic and real data.
Space-Frequency Quantization using Directionlets
2007
In our previous work we proposed a construction of critically sampled perfect reconstruction transforms with directional vanishing moments (DVMs) imposed in the corresponding basis functions along different directions, called directionlets. Here, we combine the directionlets with the space-frequency quantization (SFQ) image compression method, originally based on the standard two-dimensional (2-D) wavelet transform (WT). We show that our new compression method outperforms the standard SFQ as well as the state-of-the-art compression methods, like SPIHT and JPEG-2000, in terms of the quality of compressed images, especially in a low-rate compression regime. We also show that the order of comp…
Datorzinātne un informācijas tehnoloģijas: Datu bāzes un informācijas sistēmas: doktorantu konsorcijs. Sestā Starptautiskā Baltijas konference Baltic…
2004
The Baltic Conference on Databases and Information Systems is a biannual international forum for technical discussion among researchers and developers of database and information systems. The objective of the conference is to bring together researchers as well as practitioners and PhD students in the field of computing research that will improve the construction of future information systems. On the other hand, the conference is giving opportunities to developers, users and researchers of advanced IS technologies to present their work and to exchange their ideas and at the same time providing a feedback to database community.
Creation and cognition for humanoid live dancing
2016
Abstract Computational creativity in dancing is a recent and challenging research field in Artificial Intelligence and Robotics. We present a cognitive architecture embodied in a humanoid robot capable to create and perform dances driven by the perception of music. The humanoid robot is able to suitably move, to react to human mate dancers and to generate novel and appropriate sequences of movements. The approach is based on a cognitive architecture that integrates Hidden Markov Models and Genetic Algorithms. The system has been implemented on a NAO robot and tested in public setting-up live performances, obtaining positive feedbacks from the audience.
From Deep Learning to Deep University: Cognitive Development of Intelligent Systems
2018
Search is not only an instrument to find intended information. Ability to search is a basic cognitive skill helping people to explore the world. It is largely based on personal intuition and creativity. However, due to the emerged big data challenge, people require new forms of training to develop or improve this ability. Current developments within Cognitive Computing and Deep Learning enable artificial systems to learn and gain human-like cognitive abilities. This means that the skill how to search efficiently and creatively within huge data spaces becomes one of the most important ones for the cognitive systems aiming at autonomy. This skill cannot be pre-programmed, it requires learning…
An automatic system for humanoid dance creation
2016
Abstract The paper describes a novel approach to allow a robot to dance following musical rhythm. The proposed system generates a dance for a humanoid robot through the combination of basic movements synchronized with the music. The system made up of three parts: the extraction of features from audio file, estimation of movements through the Hidden Markov Models and, finally, the generation of dance. Starting from a set of given movements, the robot choices sequence of movements a suitable Hidden Markov Model, and synchronize them processing musical input. The proposed approach has the advantage that movement execution probabilities could be changed according evaluation of the dance executi…
Financial Fragility and Interacting Units: an Exercise
2010
This paper assumes that financial fluctuations are the result of the dynamic interaction between liquidity and solvency conditions of individual financial units. The framework is designed as a heterogeneous agent model which proceeds through discrete time steps within a finite time horizon. The interaction at the microlevel between financial units and the market maker, who is in charge of clearing the market, produces interesting complex dynamics. The model is analyzed by means of numerical simulations and agent-based computational economics (ACE) approach. The behaviour and evolution of financial units are studied for different parameter regimes in order to show the importance of the param…
Regional variation of wall shear stress in ascending thoracic aortic aneurysms.
2014
The development of an ascending thoracic aortic aneurysm is likely caused by excessive hemodynamic loads exerted on the aneurysmal wall. Computational fluid-dynamic analyses were performed on patient-specific ascending thoracic aortic aneurysms obtained from patients with either bicuspid aortic valve or tricuspid aortic valve to evaluate hemodynamic and wall shear parameters, imparting aneurysm enlargement. Results showed an accelerated flow along the outer aortic wall with helical flow in the aneurysm center for bicuspid aortic valve ascending thoracic aortic aneurysms. In a different way, tricuspid aortic valve ascending thoracic aortic aneurysms exhibited normal systolic flow without su…