An electronic apparatus and an operating method are provided. The electronic apparatus includes a storage, at least one sensor, and at least one processor configured to execute stored instructions to while the electronic apparatus is moving, capture a surrounding image by using the at least one sensor, when an unable-to-move situation occurs while the electronic apparatus is moving, generate context data including a surrounding image captured within a predetermined time from a time when the unable-to-move situation has occurred, store, in the storage, the generated context data corresponding to the unable-to-move situation having occurred, and learn the stored context data by using one or more data recognition models.

An information processing apparatus includes an estimation unit configured to estimate, based on a feature of a person of interest contained in an image captured in each of a plurality of regions and a feature of a previously set registered person, a certainty that the person of interest is the registered person, and an updating unit configured to, with respect to a first person of interest subjected to image capturing in a first region out of the plurality of regions, in a case where a period for which a state in which a certainty that a second person of interest contained in an image captured in a second region different from the first region is the registered person is larger than a threshold value is kept is longer than a predetermined period, perform updating in such a way as to lower a certainty that the first person of interest in the first region is the registered person, and, in a case where the period for which the state in which the certainty that the second person of interest is the registered person is larger than the threshold value is kept is shorter than the predetermined period, perform updating in such a way as not to lower the certainty that the first person of interest in the first region is the registered person.

According to an embodiment, an information processing apparatus includes a second recognition unit, an information processing unit, and an information output unit. The second recognition unit recognizes, by second recognition processing, a destination of an article with the destination. not recognized by first recognition processing by a first recognition unit. The information processing unit generates recognition processing information proving that the second recognition processing has been executed by the second recognition unit. The information output unit outputs the recognition processing information.

An electronic device and method for generating an augmented image. The device includes an image sensor and an electronic processor. The electronic processor is configured to receive an image, retrieve a set of keywords, and identify a first set of features within the image corresponding to at least one keyword from the set of keywords, producing first metadata. The electronic processor is configured to compress the image, identify a second set of features within the compressed image, producing second metadata, and determine missing metadata between the first metadata and the second metadata. The electronic processor is configured to generate an augmented image by associating the missing metadata to the compressed image and perform at least one selected from the group consisting of transmitting the augmented image to another device and decompressing the augmented image to create a decompressed image and presenting the decompressed image including the missing metadata.

Systems and techniques for end-to-end fuzzy entity matching are described herein. A first input and a second input may be received. The first input and the second input may be evaluated to identify common attribute types. A set of attribute entity matching models may be selected that correspond to the attribute types. The first input and the second input may be evaluated using the set of attribute entity matching models to determine a set of weighted scores for attribute pairs in the first input and the second input. The set of weighted scores may be evaluated using a table-level entity matching model to identify a common entity included in the first input and the second input. A linking dataset may be generated that includes a cross-linking facility indicating a relationship between a first entity descriptor in the first input and a second entity descriptor in the second input.

An apparatus for clinical evaluation of sensitivity of individuals to learning context provides a visual search task in which a target symbol to be located is associated with context images that cluster around the target symbol to varying degrees. Measurement of a rate of unconscious exploitation of the context symbols in finding the target symbols is used to sort the individuals into categories believed to be useful for characterizing their learning styles.

Apparatuses, systems, methods, and computer-readable media are provided for the preemptive logical configuration of vehicle control systems. A vehicle control computer may determine a location of a vehicle. The vehicle control computer may query a historical data source server for historical incident data corresponding to a first vicinity around the first location of the vehicle. Based on the historical incident data, the vehicle control computer may identify one or more driving danger areas in the first vicinity around the first location of the vehicle, wherein each of the one or more driving danger areas are associated with one or more driving hazards. The vehicle control computer may generate a configuration for vehicle operation in the first vicinity around the first location of the vehicle based on the one or more driving danger areas and may update driving logic of the vehicle with the configuration.

Described herein are techniques for generating contextually rich plant images. A number of data captures of raw plant data are generated via a sensing unit configured to navigate a growing facility. Metadata is generated and assigned to the raw plant data including at least one of: plant location, timestamp, plant identification, plant strain, facility identification, facility location, facility type, health risk factors, plant conditions, and human observations. Images generated by the sensing unit are analyzed and pixel annotations are generated in the images based on their relation to one or more plant well-being features. Data tags are generated and assigned the data captures based on an analysis of the data captures. The data tags are text phrases linking a particular data capture to a specific threat to plant well-being.

Systems as described herein may include predicting item level data based on merchant advertisement information. A transaction pattern may be detected. The merchant advertisement information may be retrieved and parsed to generate a price list. A number of transactions that each shares a common payment amount may be determined and the number may reach a threshold value. Items from the price list may be matched with the common payment amount. The transaction records may be updated to indicate likely item level transaction information. In a variety of embodiments, the likely transaction information may be presented to a user.

Systems and methods for censoring text characters in text-based data are provided. In some embodiments, an artificial intelligence system may be configured to receive text-based data and store the text-based data in a database. The artificial intelligence system may be configured to receive a list of target pattern types identifying sensitive data and receive censorship rules for the target pattern types determining target pattern types requiring censorship. The artificial intelligence system may be configured to assemble a computer-based model related to a received target pattern type in the list of target pattern types. The artificial intelligence system may be configured to use a computer-based model to identify a target data pattern corresponding to the received target pattern type within the text-based data, identify target characters within the target data pattern, and to assign an identification token to the target characters.