We define a parameterized version of the Steiner tree problem in phylogeny where the parameter measures the amount by which a phylogeny differs from "perfection." This problem is shown to be solvable in poly...
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We propose an approach to determine the occurrence of low-parametric qualitative models from images by a hypothesis-and-test approach based on the coincidence of multiple cues, thereby avoiding complete reconstruction...
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We propose an approach to determine the occurrence of low-parametric qualitative models from images by a hypothesis-and-test approach based on the coincidence of multiple cues, thereby avoiding complete reconstruction...
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We propose an approach to determine the occurrence of low-parametric qualitative models from images by a hypothesis-and-test approach based on the coincidence of multiple cues, thereby avoiding complete reconstruction of the scene. A system is presented which applies the approach to finding instances of planar surfaces, as it is important in many tasks for mobile or manipulating robots. The system uses monocularly determined L-junctions and binocular disparities. A notable feature of the approach is that it finds the most conspicuous exemplar of the model first. This property seems quite relevant for an agent using vision to guide its behaviors, since the simplest solution becomes available early on.
We stress a systems approach for research in active vision. We also argue that design and analysis of seeing agents should be accompanied by experiments, requiring implementations, i.e. a constructive approach. In par...
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We stress a systems approach for research in active vision. We also argue that design and analysis of seeing agents should be accompanied by experiments, requiring implementations, i.e. a constructive approach. In particular, we discuss two issues that we have worked with: use and integration of multiple cues and attention.
We present a computational model for attention. It consists of an early parallel stage with preattentive cues followed by a later serial stage, where the cues are integrated. We base the model on disparity image flow ...
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We present a computational model for attention. It consists of an early parallel stage with preattentive cues followed by a later serial stage, where the cues are integrated. We base the model on disparity image flow and motion. As one of the several possibilities we choose a depth-based criterion to integrate these cues, in such a way that the attention is maintained to the closest moving object. We demonstrate the technique by experiments in which a moving observer selectively mask our different moving objects in real scenes.
We report on practical experience using the Oxford BSP Library to parallelize a large electromagnetic code, the British Aerospace finite-difference time-domain code EMMA T:FD3D. The Oxford BS Library is one of the fir...
We report on practical experience using the Oxford BSP Library to parallelize a large electromagnetic code, the British Aerospace finite-difference time-domain code EMMA T:FD3D. The Oxford BS Library is one of the first realizations of the Bulk Synchronous Parallel computational model to be targeted at numerically intensive scientific (typically Fortran) computing. The BAe EMMA code is one of the first large-scale applications to be parallelized using this library, and it is an important demonstration of the cost effectiveness of the BSP approach. We illustrate how BSP cost-modelling techniques can be used to predict and optimize performance for single-source programs across different parallel platforms. We provide predicted and observed performance figures for an industrial-strength, single-source parallel code for a variety of real parallel architectures: shared memory multiprocessors, workstation clusters and massively parallel platforms.
In a recurrent artificial neural network, the units active in an attractor state typically reach their maximum activity value while the others are quiescent. In contrast, recordings of cortical cell activity in vivo r...
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In a recurrent artificial neural network, the units active in an attractor state typically reach their maximum activity value while the others are quiescent. In contrast, recordings of cortical cell activity in vivo rarely reveal cells firing at their maximum rate. This discrepancy has been one of the main arguments against using attractor networks as models of cortical associative memory. In this study we show that low-rate sustained after-activity can be obtained in a simulated network of mutually exciting pyramidal cells. This is achieved by assuming that the synapses in the network are of a saturating type. When the application of a monoamine neuromodulator is simulated, after-activity with firing rates around 60?s?1 can be produced. The firing pattern of the network was found to be similar to that of the experimentally most comparable system, the disinhibited hippocampal slice. The results obtained are robust against simulated biological variation and background noise.
作者:
Nordlund, PeterUhlin, Tomas
Department of Numerical Analysis Computing Science Royal Institute of Technology StockholmS-10044 Sweden
We present an integrated system, able to pursue a moving object by controlling a robot-head to maintain the moving object centered in the image. This system runs continuously in time and updates the object localizatio...
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The approximability of several NP maximization problems is investigated and strong lower bounds for the studied problems are proved. For some of the problems the bounds are the best that can be achieved, unless P = NP...
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作者:
Fornland, Päir
Department of Numerical Analysis and Computing Science Royal Institute of Technology StockholmS-100 44 Sweden
Autonomous vehicles need a means of detecting obstructions on its path, to avoid collision. In this paper, a novel approach to obstacle detection is presented. A camera moves on a visible ground plane with the optical...
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