Nippon Telegraph and Telephone Corporation

Yuki Kurauchi

Hitoshi Seshimo

Naoto Abe

Hiroshi Konishi

Hirofumi Abe

Shunsuke Konagai

A barrier data collection device includes a unit estimation unit that estimates, based on sensor data with position information including height at a time when a mobile body including a flying mobile body moving in the air moves, the sensor data being collected in advance about each of geographical ranges, with an estimator, about each of sets of the geographical ranges and heights included in the sensor data in a predetermined time unit, a barrier state obtained by estimating a state of which of barrier types the set is, a shape estimation unit that estimates, about a set satisfying a condition among the sets, a barrier shape based on the sensor data and an estimation result of the barrier state estimated about each of the sets in the time unit.

Barrier data collection device, barrier data collection method, and barrier data collection program

A training data generation device () according to the present invention includes a training data correction unit () configured to correct training data that is time-series data that indicates states of an object and in which a label corresponding to a state of the object is assigned to each section that corresponds to the state indicated by the label, wherein the training data correction unit () corrects a break time that divides a first section from a second section adjacent to the first section, based on time-series data in the first section and time-series data in the second section.

Learning data generation device, learning data generation method, and program

The present invention provides a data analysis system capable of performing analysis appropriately using a CNN model while reducing communication traffic. A data analysis systemincludes: an instrumentthat performs a conversion process of outputting compression data obtained as a result of processing observation data received via an input layer of a learned neural networkA using portions ranging from the input layer to a predetermined intermediate layer; and a devicethat performs an analysis process of inputting the compression data to a subsequent intermediate layer in a learned neural networkB, inputting data obtained by decoding the compression data, which is an output of the subsequent intermediate layer, to an output layer configured using a CNN model, and obtaining an analysis result of the observation data as an output of the output layer. The learned neural networksA andB are learned in advance so as to minimize an error between the output of the output layer when observation data of which the true analysis result obtained by analysis is known is input and the true analysis result and an error between the observation data and the decoded data.

Data analysis system, learning device, method, and program

A position where a user is located can be estimated easily and quickly. When a hold detection unitdetects that the user holds a mobile terminalby hand to use the mobile terminalthat is held by at least one hand of the user when used by the user and has a cameraon the surface facing the ceiling when used by the user, the estimation unitestimates a position where a ceiling is located as the position where the user is located by using an image of the ceiling captured by the camera

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Tokyo, Japan

Yuki Kurauchi