Advanced hybrid tracking through neural network regression

In the context of DOA estimation of audio sources, although the output space is highly structured, most neural network based systems rely on multi-label binary classification on

Our goal is to compute accurate trajectories with an estimate of internal and external errors as realistic as possible, taking advantage of the dense observation network

The literature on learning similarity/dissimilarity matching functions can be roughly categorized into two parts according to whether the objective is to minimize an error rate on

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

We prove the convergence of the well-known Longstaff and Schwartz algorithm when the standard least-square regression is replaced by a neural network approximation, assuming

Absolute position error as a function of distance to the SPIDAR center (before and after neural network based calibration).. To have better idea of the extent position error, we

In this study, artificial neural network model was developed for predicting the oral acute toxicity on rats of a series of 77 herbicides based on their molecular structure,

FIGURE 7 | Mean activities recorded in the ROIs of the left and right frontal lobes (left and middle columns, respectively) showing a significant main effect of movement and