An anxiety map display device according to the present disclosure includes a memory, and a processor coupled to the memory. The processor is configured to: acquire an anxiety state of a driver during driving; acquire position information of a vehicle during driving; acquire a driving situation of the vehicle during driving; generate an anxiety map indicating an anxiety occurrence position corresponding to a predetermined driving situation for the driver based on the position information and the driving situation when acquiring a predetermined anxiety state for the driver; and display the generated anxiety map for the driver as an individual anxiety map.

A sensing system determines movement and position of passengers and objects within a vehicle. The sensing system comprises a group a group of transmitting antennas operably connected to a car seat, each transmitting antenna adapted to transmit a signal that is orthogonal to each other signal transmitted during an integration period; a plurality of receiving antennas, each one of the plurality of receiving antennas adapted to receive transmitted signals; and a processor adapted to determine a measurement of the transmitted signals received and create a heatmap, wherein a heatmap summation is taken during no-touch events, compared to a baseline heatmap, and a new baseline heatmap recalibrated if a threshold is exceeded.

A computer-implemented method of converting time series data of at least one operational data source of a technical system into an image, includes providing a time series data of at least one operational data source of the technical system as a series of values of successive time stamps, wherein the values of the series of values vary over time. The method further includes the steps of assigning for each of the considered time stamps of the respective time series data either a value-depending color, a value-depending brightness, a value-depending pattern or a combination thereof to an image element of the image, and sequencing the image elements along a timeline, preferably without spaces between the image elements, to form for each time series data a set of linearly arranged image elements of the image.

This information processing device comprises: a generation circuit that, on the basis of attribute information of first image data resulting from imaging a first object in a first environment, generates second image data that reproduces an image in which a second object differing from the first object is disposed in the first environment; an evaluation circuit that evaluates the accuracy of image recognition for the second object on the basis of the second image data; and an output circuit that outputs the accuracy evaluation results.

To speed up an entire inspection by preventing display processing from delaying execution of inspection processing. An image inspection system includes an imaging unit, a first control unit configured to generate a setting screen on which a formula setting of an imaging parameter of the imaging unit, a formula setting of an inspection parameter of a workpiece image, and a display setting of an inspection result can be set in a cell of a worksheet, and display the inspection result on a display unit according to the display setting set in the cell of the worksheet, and a second control unit configured to cause the imaging unit to execute imaging processing, execute inspection processing on the workpiece image, and execute a formula calculation related to the imaging parameter and the inspection parameter set in the worksheet.

Provided is a one-shot solution to visual language reasoning. Example systems described herein decompose the challenge of visual language reasoning into two steps: translation of a graphical depiction of data (e.g., a plot or chart) into text; followed by reasoning over the translated text. In particular, example systems described herein can include a machine-learned visual-to-language conversion model that translates a graphical depiction of a dataset to a set of text descriptive of the dataset. The output of visual-to-language conversion model can then be directly used to prompt a language model, (e.g., a pretrained large language model (LLM)), exploiting the few-shot reasoning capabilities of the language model.

An information processing device (10) includes: a waveform data generation unit (12) that, from action data related to acquired action of a user and including a type and an execution time information of the action, obtains a timing in time series of an event related to action characteristics of the user and connects the timings adjacent in time series with a predetermined waveform, to generate waveform data for each action; and an image generation unit (13) that generates a two-dimensional image representing the action characteristics of the user by performing power spectrum imaging on the generated waveform data.

Apparatus for generating electro-anatomical mapping and methods used therein include a processor and a memory connected to the processor, wherein the memory contains instructions configuring the processor to receive input data, generate, using at least a machine learning model, an electro-anatomical mapping as a function of the input data, and display the electro-anatomical mapping using a user interface, wherein receiving the input data includes receiving, from an imaging device, at least a medical image and receiving, from a signal capturing device, at least an electrogram, wherein the at least a machine learning model is trained using electro-anatomical mapping training data including exemplary medical images and exemplary electrograms as input correlated to exemplary electro-anatomical mappings as output.

Methods and systems for modifying a digital image are described herein. The method can include performing vividness scoring for a plurality of pixels of the digital image, determining one or more candidate pixels based on the vividness scoring for the plurality of pixels, and agglomerating the one or more candidate pixels into one or more suggested agglomerates. The method can also include determining at least one subject of the digital image, removing at least one agglomerate from the one or more suggested agglomerates based on at least one of the at least one subject of the digital image or one or more characteristics of the at least one agglomerate, generating a modified digital image with the one or more suggested agglomerates modified, and outputting the modified digital image.

A computer implemented method is provided. The method, comprises: receiving from an autonomous vehicle sensor data, wherein the sensor data is indicative of an environment in which the vehicle is currently located or was previously located. The method further comprises receiving or determining additional data associated with at least one of: the sensor data, the vehicle, or the environment, wherein the additional data is different from the sensor data. The method further comprises displaying, on a display, an output comprising a representation of the sensor data. The method further comprises determining, based at least in part on the additional data, a reliability metric, the reliability metric being indicative of how reliable the sensor data is at representing the environment in which the vehicle is located at a current time. The method further comprises causing the output on the display to be based at least in part on the reliability metric.