Denso It Laboratory, Inc.

Jingo Adachi

Chiharu Yamano

A technique for stable and fast computation of a variance representing a confidence interval for an estimation result in an estimation apparatus using a neural network including an integrated layer that combines a dropout layer for dropping out part of input data and an FC layer for computing a weight is provided. When input data having a multivariate distribution is supplied to the integrated layer, a data analysis unitdetermines, based on a numerical distribution of terms formed by respective products of each vector element of the input data and the weight, a data type of each vector element of output data from the integrated layer. An estimated confidence interval computation unitapplies an approximate computation method associated with the data type, to analytically compute a variance of each vector element of the output data from the integrated layer based on the input data to the integrated layer.

Information estimation apparatus and information estimation method

A technique of estimating a surrounding environment with higher accuracy from observation data obtained by using sensing equipment is disclosed. According to the technique, a certain pixel in an observation data space which includes the observation data obtained by a sensoris sampled. With regard to the sampled pixel, a grid-unspecified logarithm-likelihood ratio indicating whether a received signal is a signal reflected from a detected object is calculated from an intensity value of the received signal, and a distribution function of an angle indicating the degree of dispersion centering on an azimuth angle is calculated. Then, the product of the grid-unspecified logarithm-likelihood ratio and the distribution function is calculated and thereby a calculation for updating an occupation probability of the object is performed across a plurality of grids in an occupancy grid map by using a value obtained by dispersing the likelihood using the distribution function.

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Tokyo, Japan

Jingo Adachi