Results 241 to 250 of about 1,168,555 (296)

Propagation of Interpreter Errors by Ambient AI Scribes: Study Using Simulated Clinical Encounters. [PDF]

open access: yesJMIR Med Inform
Rabotin A   +7 more
europepmc   +1 more source

Shift-and-Propagate

Journal of Heuristics, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Timo Berthold, Gregor Hendel
openaire   +3 more sources

Propagation of inhibition

Vision Research, 1981
Abstract Visual spatio-temporal inhibition effects were investigated with the aid of “jumping flashes” (pairs of point flashes, separated in time and space). Plots of the visibility of the jumping flashes against the interval time, produced visibility curves in which two dips (representing inhibition effects) were observed.
G J, van der Wildt, P C, Vrolijk
openaire   +2 more sources

Propagation techniques.

2008
Abstract This chapter discusses various peach propagation techniques, covering the following aspects: nursery seedling propagation (nursery site and soil, and propagation from seed); nursery hardwood cutting; greenhouse semi-hardwood cutting; micropropagation (preparation of the propagation material, explant disinfection and setting-up aseptic ...
LORETI, FILIBERTO, MORINI, STEFANO
openaire   +2 more sources

Learning by Propagability

2008 Eighth IEEE International Conference on Data Mining, 2008
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and optimal feature representation can constitute a harmonic system, namely, the data labels are invariant with respect to the propagation on the similarity-graph constructed by ...
Bingbing Ni   +3 more
openaire   +1 more source

Back propagation and forward propagation

[Proceedings 1992] IJCNN International Joint Conference on Neural Networks, 2003
The authors analyze the validity of the pessimistic views of M.L. Minsky and S.A. Papert (Perceptrons: An Intro. to Comput. Geom., MIT Press, Cambridge, MA, 1969) on the possibility of training multi-layer perceptrons. In particular, they show that it was possible, using the simplex algorithm of J.A. Nelder and R. Mead (Comput. Journ., vol.8, pp.308-13,
L.J. Buturovic, L.T. Citkusev
openaire   +1 more source

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