Screen Holdings Co., Ltd.

Kazuhiro Kitamura

Hiroaki Kakuma

Atsushi Imamura

Itaru Furukawa

Kiyotaka Kasubuchi

Manri Terada

Koki Umehara

Akiko Yoshida

Kiyotaka Miyai

A similarity calculation apparatus according to the present invention includes: a name acquisition unit configured to acquire a first group name to which each word belonging to a first synonym group belongs and a second group name to which each word belonging to a second synonym group belongs; a name set generation unit configured to generate a first group name set and a second group name set; and a similarity calculation unit configured to calculate similarity between the first group name set and the second group name set. Therefore, even when a plurality of synonym groups are created, terms can be effectively unified.

Similarity calculation apparatus, recording medium, and similarity calculation method

A method for building an image determination model that determines whether a print image is a good image or a failure image includes a step of determining whether the print image is a high-density image or a low-density image; a step of generating teaching data by combining pseudo-failure data with to-be-combined image data, based on a result of the determination; and a step of performing machine learning. Regarding the combining of the pseudo-failure data, for a print image determined to be the high-density image, low-density pseudo-failure data is combined with to-be-combined image data, and for a print image determined to be the low-density image, high-density pseudo-failure data is combined with to-be-combined image data.

Method for building image determination model, image determination model, and image determination method

A method of estimating the congestion degree and the number of people with high accuracy and at a low cost, without requiring a surveillance camera, is provided. Provided are a congestion degree estimating step of estimating a congestion degree based on sensor information (such as acceleration information) of a portable terminal device, an average congestion degree calculating step of calculating an average congestion degree for each mesh (reference range) set in advance, based on the congestion degree estimated in the congestion degree estimating step for a plurality of portable terminal devices, and an estimated number-of-people calculating step of calculating an estimated number of people for each mesh by multiplying the average congestion degree calculated in the average congestion degree calculating step by a base number of people (maximum number of accommodated people) determined in advance for each mesh.

Congestion degree estimation method, number-of-people estimation method, congestion degree estimation program, number-of-people estimation program and number-of-people estimation system

A displacement detecting apparatus according to the invention comprises: a mover which moves and positions a positioning object; an imager which images an image including an imaging object which is the positioning object or an object displacing integrally with the positioning object as the positioning object is displaced; and a displacement detector which detects the imaging object from the image imaged by the imager and detects a displacement of the positioning object based on the position of the imaging object detected in the image, wherein the displacement detector obtains a displacement amount of the positioning object with respect to a predetermined reference position from a value obtained by multiplying a distance between the position of the imaging object and the reference position in the image by a coefficient determined according to size of the imaging object in the image.

Displacement detecting apparatus, displacement detecting method and substrate processing apparatus

This invention is to provide a technique capable of detecting a displacement of a positioning object with respect to a reference position in an actual space with high accuracy. A position of an imaging object detected in an imaged image is converted into a displacement of the positioning object with respect to the reference position in the actual space based on conversion information representing a correlative relationship between the position of the imaging object in the image and the displacement of the positioning object from the reference position. The conversion information is determined in advance based on positions of the imaging object detected from a plurality of images respectively imaged with the positioning object positioned at each of a plurality of imaging positions.

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Kyoto, Japan

Kazuhiro Kitamura