Provided is an image processing apparatus, including: an acquisition unit configured to acquire information on a layer boundary in tomographic structure of a current subject to be inspected; a determination unit configured to determine a depth range relating to a current en-face image of the subject to be inspected based on information indicating a depth range relating to a past en-face image of the subject to be inspected and the information on the layer boundary; and a generation unit configured to generate the current en-face image through use of data within the depth range relating to the current en-face image among pieces of three-dimensional data acquired for the current subject to be inspected.

We present several unique techniques for using touch sensor arrays to detect fingerprints and authenticate a user.

A computer-implemented method of using a machine learning model to categorize a sample in digital pathology may include receiving one or more cases, each associated with digital images of a pathology specimen; identifying, using the machine learning model, a case as ready to view; receiving a selection of the case, the case comprising a plurality of parts; determining, using the machine learning model, whether the plurality of parts are suspicious or non-suspicious; receiving a selection of a part of the plurality of parts; determining whether a plurality of slides associated with the part are suspicious or non-suspicious; determining, using the machine learning model, a collection of suspicious slides, of the plurality of slides, the machine learning model having been trained by processing a plurality of training images; and annotating the collection of suspicious slides and/or generating a report based on the collection of suspicious slides.

A fingerprint authentication method includes a first step of acquiring partial fingerprint measurement data for a part of a fingerprint, and a second step of calculating a matching rate by comparing the partial fingerprint measurement data with reference comparison data selected among a plurality of partial fingerprint registration data, each partial fingerprint registration data corresponding to a part of a fingerprint. The method further includes a third step of determining whether the matching rate is equal to or greater than an authentication threshold and a fourth step of determining, based on a result in the third step, a success of the authentication, or repeating the second and third steps by selecting new reference comparison data based on whether or not the matching rate is equal to or greater than a preset threshold smaller than the authentication threshold.

The various embodiments described herein include methods, devices, and systems for providing event alerts. In one aspect, a method includes: (1) obtaining a video feed, the video feed comprising a plurality of images; and, (2) for each image, analyzing the image to determine whether the image includes a person, the analyzing including: (a) determining that the image includes a potential instance of a person by analyzing the image at a first resolution; (b) in accordance with the determination that the image includes the potential instance, denoting a region around the potential instance; (c) determining whether the region includes an instance of the person by analyzing the region at a second resolution, greater than the first resolution; and (d) in accordance with a determination that the region includes the instance of the person, determining that the image includes the person.

An electronic apparatus includes an authenticator configured to identify registered finger information that coincides with detected finger information by matching the detected finger information with the plurality of registered finger information in a predetermined order, an executor configured to execute a function corresponding to the registered finger information identified by the authenticator, a user identifier configured to identify the actual user among the plurality of registered users by acquiring user identification information representing the actual user or by performing a determination process configured to determine the actual user, and a controller configured to change the predetermined order according to the actual user identified by the user identifier.

A translation apparatus includes a translation unit which translates content of a document into a different language, a history creating unit which, in translation of the content from a first language into a second language, creates history information including a correspondence between original text in the first language and translated text in the second language, an extraction unit which, in translation of the content from the second language into another language, if content (present content) of the document in the second language is present in the history information, extracts content (absent content) that is not present in the history information, and a combining unit which combines a translation result obtained by translating the present content from the second language into the other language, with a replacement result obtained by replacing the absent content from the second language to the other language based on the history information.

A method for driver identification including recording a first image of a vehicle driver; extracting a set of values for a set of facial features of the vehicle driver from the first image; determining a filtering parameter; selecting a cluster of driver identifiers from a set of clusters, based on the filtering parameter; computing a probability that the set of values is associated with each driver identifier of the cluster; determining, at the vehicle sensor system, driving characterization data for the driving session; and in response to the computed probability exceeding a first threshold probability: determining that the new set of values corresponds to one driver identifier within the selected cluster, and associating the driving characterization data with the one driver identifier.

In general, one innovative aspect of the subject matter described in this specification can be embodied in a computer-implemented method. The method includes, detecting, by an imaging device, the presence of an object to be imaged. The method further includes, measuring, by the imaging device, a first characteristic of the object to be imaged, and measuring, by the imaging device, a second characteristic of the object to be imaged. The method further includes, determining, by a computing device, that at least one of the first characteristic of the object or the second characteristic of the object exceeds a threshold; and in response to determining, indicating, by the computing device, whether the object to be imaged is one of a spoofed object or an actual object.

A method for image analysis, including recording an image sequence at a vehicle system mounted to a vehicle; automatically detecting an object within the image sequence with a detection module; automatically defining a bounding box about the detected object within each image of the image sequence; modifying the image sequence with the bounding boxes for the detected object to generate a modified image sequence; at a verification module associated with the detection module, labeling the modified image sequence as comprising one of a false positive, a false negative, a true positive, and a true negative detected object based on the bounding box within at least one image of the modified image sequence; training the detection module with the label for the modified image sequence; and automatically detecting objects within a second image sequence recorded with the vehicle system with the trained detection module.