Automated Reconstruction of Dendritic and Axonal Trees by Global Optimization with Geometric Priors
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We describe in this document our preliminary results regarding the tracking of dendrites spreading from a neuron in confocal microscope im- ages. When using a small number of image layers, we obtain good results by combining a EM-based local estimate of th ...
In this work we present a novel concept of augmenting a search tree in a packet-processing system with an dditional data structure, a Network of Shortcuts, in order to adapt the search to current input traffic patterns and significantly speed-up the freque ...
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most problems of interest, the optimal solution involves planning in an infinite ...
Monadic query languages over trees currently receive considerable interest in the database community, as the problem of selecting nodes from a tree is the most basic and widespread database query problem in the context of XML. Partly a survey of recent wor ...
Scalable mechanisms to support efficient key-based search in distributed systems are an important part of the infrastructure of peer-to-peer systems and global information systems. They received substantial attention both in information and communication s ...
This paper proposes a tree-based pursuit algorithm that efficiently trades off complexity and approximation performance for overcomplete signal expansions. Finding the sparsest representation of a signal using a redundant dictionary is, in general, a NP-Ha ...
A novel current-mode, binary-tree WTA / LTA circuit for application in analog Kohonen neural networks has been presented. In the proposed circuit input currents are first converted to step signals with equal amplitudes and different delays that are proport ...
Technical University of Lodz, Department of Microelectronics & Computer Science2009
This paper proposes a tree-based pursuit algorithm that efficiently trades off complexity and approximation performance for overcomplete signal expansions. Finding the sparsest representation of a signal using a redundant dictionary is, in general, a NP-Ha ...
Building good sparse approximations of functions is one of the major themes in approximation theory. When applied to signals, images or any kind of data, it allows to deal with basic building blocks that essentially synthesize all the information at hand. ...
In a bog site in way of paludification, a pine stand is declining, which presently is an infrequent phenomenon on the Swiss Jura scale. A transect was positioned in the bog, from the external and driest part (pine-spruce stand) towards the central and wett ...