LEARNING DEVICE, FORECASTING DEVICE, METHOD, AND PROGRAM

WIPO Patent Application WO/2019/235370

A1

The objective of the present invention is to assign with good precision a movement means label to a movement trajectory created by an unknown movement means by using a classifier for which learning has been completed. For a movement trajectory that incudes coordinates for each time of day and that is created by an unknown movement means, the movement trajectory is filtered by using a parameter pertaining to a Gaussian process and a parameter pertaining to noise, which have been learned in advance for each movement means label; for each movement means label a feature vector is extracted from the filtering result for the movement trajectory; a classifier that has been learned in advance for each movement means label and is for identifying which movement trajectory the movement means label is for, is used to calculate a probability indicating which movement trajectory the movement means label is for; and a predicted label for the movement trajectory is output on the basis of the calculation result.

WO/2022/108509	METHOD AND SYSTEM FOR COMPLIANCE DETERMINATION
JP6900724	Learning programs, learning methods and learning devices
WO/2023/170896	LEARNING DEVICE, INFERENCE DEVICE, LEARNING METHOD, AND INFERENCE METHOD

TANAKA YUSUKE (JP)
NISHIMURA TAKUYA (JP)
TODA HIROYUKI (JP)

PCT/JP2019/021643

December 12, 2019

May 30, 2019

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NIPPON TELEGRAPH & TELEPHONE (JP)

G06N20/00

JP2016105231A

2016-06-09

ENDO, YUKI ET AL.: "Feature Extraction from GPS Logs Using Representation Learning for Transportation Mode Estimation", vol. 8, no. 3, 1 September 2015 (2015-09-01), pages 12 - 23, XP055661573, Retrieved from the Internet

TAIYO, NAKAJIMA & KATO (JP)

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