Nitto-Denko Corporation

Yoichi Kigawa

Kazumasa Okada

Nobuyuki Kozonoi

Tatsuya Kitahara

Yatfei Chan

Naruyoshi Itadani

A BRDC sign detecting system includes: a processor, and a memory storing program instructions that cause the processor to obtain, with respect to a bovine developing bovine respiratory disease complex (BRDC) within a time period required for a fattening process, data indicating a condition of the bovine during a predetermined time period in which the bovine did not yet develop the BRDC, and obtain data indicating a condition, during a predetermined time period, of a bovine that has not developed BRDC perform machine learning with respect to a correspondence relation between the obtained data indicating the condition during the predetermined time period and information indicating whether BRDC is developed, and infer, by inputting data indicating a condition of a new bovine during the predetermined time period into a learned model generated by performing the machine learning, information indicating whether the new bovine will develop BRDC and output an inference result.

BRDC sign detecting system

An inspection system includes a memory; and a processor, wherein the memory is configured to hold an image reproducing model trained to reproduce, from a first masked image generated by masking part, of a first image determined as including no defect from among images that capture an object to be inspected, the first image before being masked, and wherein the processor is configured to determine, based on a reproduced image reproduced by inputting a second masked image generated by masking part of a second image that captures a new object to be inspected into the image reproducing model, and the second image, whether the second image includes a defect.

Inspection system, inspection method, and inspection program

Provided is an image classification system for classifying an input image including: a network constructed so that feature amount extraction processing and fully connected processing are executed on input image data; a path extracting means configured to extract a processing path in the network; and a determination module configured to compare the processing path extracted by the path extracting means and a plurality of setting paths set in advance in association with classes to set a class associated with a matched path as a class of the input image.

Image classification system and method, classification data creation system and method, and storage medium

An inspection apparatus configured to inspect a target for defects, including: an image capturing unit capable of capturing an image of the target as image information having color information including RGB values; and a determination unit configured to determine presence or absence of defects in the target based on the color information of the image information of the image captured by the image capturing unit, wherein the determination unit is configured to define, for each pixel, criteria for determining presence or absence of defects in each pixel of the image information, based on the color information in a defect-free region of the target captured by the image capturing unit, and to filter all pixels in the image information of the image captured by the image capturing unit so as to determine presence or absence of defects in each pixel, based on the defined criteria.

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Ibaraki, Japan

Yoichi Kigawa