Abstract: A notification control unit includes a notification setting information selection unit, a notification setting information storage unit, a notification setting information setting unit, and the notification execution unit. Notification setting information is associated with individual setting information to be preserved in the notification setting information storage unit. The notification execution unit performs a notification according to setting of use-notification setting information which is selected by using the individual setting information by the notification setting information selection unit. The created or changed notification setting information is preserved in the notification setting information storage unit.

Abstract: Provided is an in-vehicle stereo camera which enables the continuation of automated driving if failures occur during imaging. A pair of captured images 301, 302, which is captured by a pair of imaging units so that both contain an overlapping region, are acquired (S201), it is determined whether an abnormal region is present in at least one of the pair of captured images, and if an abnormal region is present, the degree of impact from the abnormal region on an object recognition process of an object recognition unit is diagnosed (S202), and the processing content of the object recognition process is updated according to the degree of impact (S203).

Abstract: A device includes an image sensor and a processor to: receive training images that each include multiple visual features and an ROI; receive indications of locations of ROIs within each training image; perform at least one transform on the multiple visual features and ROI of at least one training image to align the multiple visual features and ROIs among all of the training images to identify a common set of visual features present within all of the training images; derive a converged ROI from at least a portion of the ROI of at least one training image; and generate an anchor model based on the converged ROI and the common set of visual features, wherein the common set of visual features defines the anchor and are each specified relative to the converged ROI, and the anchor model is used to derive a location of a candidate ROI in an image.

Abstract: Presented are concepts for feature identification in medical imaging of a subject. One such concept processes a medical image with a Bayesian deep learning network to determine a first image feature of interest and an associated uncertainty value, the first image feature being located in a first sub-region of the image. It also processes the medical image with a generative adversarial network to determine a second image feature of interest within the first sub-region of the image and an associated uncertainty value. Based on the first and second image features and their associated uncertainty values, the first sub-region of the image is classified.

Abstract: When measuring a mass-produced work piece using a measuring X-ray CT apparatus, which is configured to emit X-rays while rotating a work piece that is arranged on a rotary table and to reconstruct a projection image thereof to generate volume data of the work piece, the present invention assigns values to volume data for a predetermined work piece and stores the same as master data; obtains volume data for a mass-produced work piece under identical conditions to the predetermined work piece; measures the volume data and obtains an X-ray CT measured value for the mass-produced work piece; and corrects the X-ray CT measured value for the mass-produced work piece using the master data.