Search results for "Artificial Intelligence"
showing 10 items of 6122 documents
Rethinking the sGLOH Descriptor
2018
sGLOH (shifting GLOH) is a histogram-based keypoint descriptor that can be associated to multiple quantized rotations of the keypoint patch without any recomputation. This property can be exploited to define the best distance between two descriptor vectors, thus avoiding computing the dominant orientation. In addition, sGLOH can reject incongruous correspondences by adding a global constraint on the rotations either as an a priori knowledge or based on the data. This paper thoroughly reconsiders sGLOH and improves it in terms of robustness, speed and descriptor dimension. The revised sGLOH embeds more quantized rotations, thus yielding more correct matches. A novel fast matching scheme is a…
Case-Sensitivity of Classifiers for WSD: Complex Systems Disambiguate Tough Words Better
2007
We present a novel method for improving disambiguation accuracy by building an optimal ensemble (OE) of systems where we predict the best available system for target word using a priori case factors (e.g. amount of training per sense). We report promising results of a series of best-system prediction tests (best prediction accuracy is 0.92) and show that complex/simple systems disambiguate tough/easy words better. The method provides the following benefits: (1) higher disambiguation accuracy for virtually any base systems (current best OE yields close to 2% accuracy gain over Senseval-3 state of the art) and (2) economical way of building more effective ensembles of all types (e.g. optimal,…
Near-infrared imaging and structured light ranging for automatic catheter insertion
2006
Vein localization and catheter insertion constitute the first and perhaps most important phase of many medical procedures. Currently, catheterization is performed manually by trained personnel. This process can prove problematic, however, depending upon various physiological factors of the patient. We present in this paper initial work for localizing surface veins via near-infrared (NIR) imaging and structured light ranging. The eventual goal of the system is to serve as the guidance for a fully automatic (i.e., robotic) catheterization device. Our proposed system is based upon near-infrared (NIR) imaging, which has previously been shown effective in enhancing the visibility of surface vein…
OPETH: Open Source Solution for Real-Time Peri-Event Time Histogram Based on Open Ephys
2019
Single cell electrophysiology remains one of the most widely used approaches of systems neuroscience. Decisions made by the experimenter during electrophysiology recording largely determine recording quality, duration of the project and value of the collected data. Therefore, online feedback aiding these decisions can lower monetary and time investment, and substantially speed up projects as well as allow novel studies otherwise not possible due to prohibitively low throughput. Real-time feedback is especially important in studies that involve optogenetic cell type identification by enabling a systematic search for neurons of interest. However, such tools are scarce and limited to costly co…
GTVcut for neuro-radiosurgery treatment planning: an MRI brain cancer seeded image segmentation method based on a cellular automata model
2018
Despite of the development of advanced segmentation techniques, achieving accurate and reproducible gross tumor volume (GTV) segmentation results is still an important challenge in neuro-radiosurgery. Nowadays, magnetic resonance imaging (MRI) is the most prominent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a minimally invasive technology for dealing with inaccessible or insufficiently treated tumors with traditional surgery or radiotherapy. During a treatment planning phase, the GTV is generally contoured by experienced neurosurgeons and radiation oncologists using fully manual segmentation procedures on MR images. Unf…
Modeling Local Social Migrations: A Cellular Automata Approach
2015
In local social migrations, agents move from their initial location looking for a better local social environment. Social migrations processes do not change the number of social agents of a given type (i.e., the empirical distribution of the population) but their spatial location. Although cellular automata seems to appear as a natural approach to model of social migrations, the evolution of the configuration through a cellular automata might induce a new configuration wherein the number of agents of each type might be actually modified. This article provides a characterization of these cellular automata rules such that for any initial empirical distribution, the evolution of the configurat…
Constraint Cellular Automata for Urban Development Simulation: An Application to the Strasbourg-Kehl Cross-Border Area
2017
AcknowledgementsThe research presented in this chapter is part of the Smart. Boundary project supported by the Fonds National de la Recherche in Luxembourg and CNRS in France (ref. INTER/CNRS/12/02). The authors would like also to thank the Grasp Program of LISER for allowing cross-collaboration between the two teams based in Luxembourg and France.; International audience; Urban sprawl and space consumption have become key issues in sustainable territorial development. Traditional planning approaches are often insufficient to anticipate their complex spatial consequences, especially in cross-border areas. Such complexity requires the use of dynamic spatial simulations and the development of…
Computation of inverse functions in a model of cerebellar and reflex pathways allows to control a mobile mechanical segment.
2003
Abstract The command and control of limb movements by the cerebellar and reflex pathways are modeled by means of a circuit whose structure is deduced from functional constraints. One constraint is that fast limb movements must be accurate although they cannot be continuously controlled in closed loop by use of sensory signals. Thus, the pathways which process the motor orders must contain approximate inverse functions of the bio-mechanical functions of the limb and of the muscles. This can be achieved by means of parallel feedback loops, whose pattern turns out to be comparable to the anatomy of the cerebellar pathways. They contain neural networks able to anticipate the motor consequences …
Cerebellar learning of bio-mechanical functions of extra-ocular muscles: modeling by artificial neural networks
2003
A control circuit is proposed to model the command of saccadic eye movements. Its wiring is deduced from a mathematical constraint, i.e. the necessity, for motor orders processing, to compute an approximate inverse function of the bio-mechanical function of the moving plant, here the bio-mechanics of the eye. This wiring is comparable to the anatomy of the cerebellar pathways. A predicting element, necessary for inversion and thus for movement accuracy, is modeled by an artificial neural network whose structure, deduced from physical constraints expressing the mechanics of the eye, is similar to the cell connectivity of the cerebellar cortex. Its functioning is set by supervised reinforceme…
Simulations of the cultured granule neuron excitability
2003
Abstract We have developed a biophysical model of a cultured rat cerebellar granule neuron and simulated its excitability under different experimental conditions. The basic excitability properties of such a small neuron; the specific action potential waveforms, the overall firing patterns induced by current stimulations, and the linear frequency-current relation, are the main model constraints. Simulations show that for a one-compartmental granule neuron model, the constraints are met using six voltage- and time-dependent ion channel types and calcium dynamics linked to BK Ca ion channel function. This kind of model of a single neuron forms a solid basis for building the increasingly more c…