Honda Motor Co., Ltd.

Rib Laboratory, Inc.

Toshikazu Karube

Tsuyoshi Eguchi

Setsuro Mori

Kosuke Jojima

Seiya Shirakawa

Takanori Yamazaki

An autoencoder is caused to learn based on data of a majority class of imbalanced data. The imbalanced data is input to the autoencoder that has learned, and an error in a predetermined parameter between an input image data and an output image data is acquired. Data of each class is extracted as teacher data such that the number of pieces of first class data counted in descending order of the size of the obtained error among the first class data and the number of pieces of second class data are balanced. A convolutional neural network is caused to learn the teacher data to obtain a learning model.

Learning model generating method and inspection device

A teacher data generating method includes: causing a generation model to perform learning by using a learning image in which boundary information indicating in a chromatic color a range of a defect is superimposed on a defective product image in a gray scale so as to generate a generated defect image including a new image of a defect in the gray scale and an image of the boundary information in the chromatic color; generating the generated defect image by using the generation model; extracting a pixel having a pixel value corresponding to the chromatic color from the generated defect image, extracting the boundary information corresponding to the generated defect image, and acquiring a gray scale defect image without including an image of the boundary information; calculating a coordinate of the boundary information; and associating the gray scale defect image with the coordinate to obtain defective product teacher data.

Teacher data generating method and generating device

Preparing actual defective product data and non-defective product data, causing a deep generation model to learn the data and to generate latent variables in which features of the non-defective product data and the actual defective product data are mixed, causing a classification model to learn the latent variables to generate a classified non-defective product and defective product latent variable, deleting the non-defective product latent variable from the classified non-defective product and defective product latent variable to output the defective product latent variable including a gray latent variable, causing a distance learning model to learn the defective product latent variable and the non-defective product latent variable and to delete the gray latent variable, and causing the deep generation model to learn the defective product latent variable that has been obtained and to generate the pseudo defective product data greater in number than the actual defective product data.

Pseudo defective product data generation method

A pinch detection device at an opening/closing section has a very simple structure that can surely detect a pinch without faulty operation in a vehicle whose power supply voltage greatly fluctuates. The pinch detection device includes a sensor for detecting displacement of an opening/closing section of a vehicle to be opened/closed by a motor, and a time counter for counting a relative time adjusted according to a fluctuation in a power supply voltage. The pinch detection device also has a pinch detector for detecting a pinch of a foreign matter at the opening/closing section according to a change in a relative speed obtained based on a change in the displacement on a basis of the relative time.

Pinch detection device at opening/closing section, vehicle having the device, and method for detecting pinch at the opening/closing section

A control device at an opening/closing section of a vehicle and a method for controlling the opening/closing section of the vehicle control a motor so that a pinch at the opening/closing section is determined accurately. The control device includes a pinch determination device that is mounted to the motor for opening/closing the opening/closing section of the vehicle and determines a pinch of a foreign object based on a change in the rotation number of the motor, and demagnetization pulse applying device for supplying power with reverse polarity to the motor in a pulse-like manner at the completion of the opening/closing.

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Saitama, Japan

Toshikazu Karube