Abstract: A method and system for detecting defects in a specimen, the method comprising: obtaining an image comprising a plurality of pixels of a specimen part; processing the image according to a detection recipe to derive information related to potential defects in the specimen, the information comprising a first data set informative of first locations identified, in accordance with the detection recipe as locations of potential defects, and a second data set informative of second locations not identified as locations of potential defects; receiving data specifying targeted locations of interest within the part of the specimen; when the first data set is not informative of each targeted location, generating a third data set by adding to the first data set information related to the missing targeted location from the second data set, the information bearing an indication that it corresponds to a targeted location; and outputting the third data set.

Abstract: An electronic device and method are disclosed herein. The electronic device includes: a processor, and a memory operatively connected to the processor.

Abstract: An information processing method includes, by using a computer: acquiring an annotation skill of an operator who provides annotation information to image; acquiring annotation-target image having an image feature identified based on the annotation skill; acquiring an annotation result attained by the operator for the annotation-target image; and updating the annotation skill using the annotation result and reference annotation information corresponding to the image feature.

Abstract: A method for processing medical image data comprises: inputting medical image data to a variational autoencoder configured to reduce a dimensionality of the medical image data to a latent space having one or more latent variables with latent variable values, such that the latent variable values corresponding to an image with no tissue of a target tissue type fit within one or more clusters; determining a probability that the latent variable values corresponding to the medical image data fit within the one or more clusters based on the latent variable values; and determining that a tissue of the target tissue type is present in response to a determination that the medical image data have less than a threshold probability of fitting within any of the one or more clusters based on the latent variable values.

Abstract: A control device acquires a plurality of observation signals observed using a plurality of projection patterns having different spatial frequencies, as observation signals for a measurement point on a measurement object. The control device repeatedly executes processing for estimating two component signals included in each observation signal, so as to separate the observation signal into two component signals, and calculate a three-dimensional position of the measurement point based on the phases of the separated component signals.

Abstract: An apparatus for recognizing a license plate of a vehicle, the apparatus having an interface for reading-in an image of a surrounding of an optical sensor, the image originating from the optical sensor picturing at least the vehicle having a detectable license plate. The apparatus further comprises a unit for analyzing the image using a convolutional neural network, the convolutional neural network having at least two separated symbol identification branches, each of the separated symbol identification branches being configured for identifying one of several symbols of the license plate and/or the convolutional neural network having a country identification branch being separated from the symbol identification branches, the country identification branch being configured for identifying the country having issued the license plate.