A method of adjusting mental state includes acquiring video data of a first individual and a second individual, extracting image data and audio data from the video data, extracting first image data of the first individual from the video data, extracting first audio data of the first individual from the video data, extracting second image data of the second individual from the video data, extracting first semantic text data from the first audio data, and extracting second semantic text data from the second audio data. The method further includes identifying first and second sets of features, predicting a first baseline mental state, predicting a second baseline mental state, predicting an average baseline mental state, identifying a target mental state, simulating a predicted path from the average baseline mental state toward the target mental state, and outputting an indication of one or more actions for adjusting the baseline mental state.

A system and a method of tracking an input sign for an extended reality are provided, wherein the method including: obtaining an image; detecting for a handheld device and a hand in the image; in response to a first bounding box of the hand and a second bounding box of the handheld device being detected, detecting at least one joint of the hand from the image; performing a data fusion of the first bounding box and the second bounding box according to the at least one joint to obtain the input sign; and outputting a command corresponding to the input sign via the output device.

A hybrid operation of a license plate recognition (LPR) system and infrastructure monitoring is provided. The system takes advantage of a first mode of operation of the LPR system, by running an infrastructure analytical tool which gathers infrastructure images in parallel with license plate detection. Analytics are applied, via a cloud based analytics engine, to provide detection of infrastructure anomalies, and prediction of potential infrastructure incidents. The system further generates a trigger alert warning of a potential infrastructure incident and recommendation to address the potential infrastructure incident.

A method and system for fusion of multi-modal volumetric images is disclosed. A first image acquired using a first imaging modality is received. A second image acquired using a second imaging modality is received. A model and of a target anatomical structure and a transformation are jointly estimated from the first and second images. The model represents a model of the target anatomical structure in the first image and the transformation projects a model of the target anatomical structure in the second image to the model in the first image. The first and second images can be fused based on estimated transformation.

The technology disclosed relates to authenticating users using a plurality of non-deterministic registration biometric inputs. During registration, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate sets of feature vectors. The non-deterministic biometric inputs can include a plurality of face images and a plurality of voice samples of a user. A characteristic identity vector for the user can be determined by averaging feature vectors. During authentication, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate a set of authentication feature vectors. The sets of feature vectors are projected onto a surface of a hyper-sphere. The system can authenticate the user when a cosine distance between the authentication feature vector and a characteristic identity vector for the user is less than a pre-determined threshold.

Provided are an information processing device, an information processing method, a computer program, and an interaction system for processing an interaction with a user. The information processing device includes a determination section that determines a state or a tendency of a user, and a decision section that decides an output to the user on the basis of a determination result obtained by the determination section. The determination section determines the state or the tendency of the user on the basis of a sensing result on the user or operation of an apparatus being used by the user. Further, the decision section decides a timing for talking to the user, a condition for talking to the user, or a speech for talking to the user.

This application provides to a method for identifying one or more prostate tissue samples in a database that are closest to a test prostate sample, which can be used to aid pathologists when examining prostate tissues to attain reliable and consistent diagnoses of prostate cancer. Also provided are databases and computer algorithms that can be used with such methods.

A farming machine identifies and treats a plant as the farming machine travels through a field. The farming machine includes a pair of image sensors for capturing images of a plant. The image sensors are different, and their output images are used to generate a depth map to improve the plant identification process. A control system identifies a plant using the depth map. The control system captures images, identifies a plant, and actuates a treatment mechanism in real time.

A method comprises receiving an image of a road captured by a vehicle driving on the road, receiving a map of the road, the map comprising a road geometry of the road, obtaining an edge map of the road based on the image of the road, inputting the image, the map of the road, and the edge map into a trained regressor neural network, determining an estimated snow depth for each of one or more lanes of the road based on an output of the regressor neural network, and transmitting the estimated snow depth to an edge computing device.

A fused image of the person's hand is accessed, the fused image having been generated using a segmented graylevel image and a segmented color image. The hand in the fused image is identified. One or more finger tips and one or more finger valleys in the fused image are identified. One or more fingers of the hand are segmented, based on the identified finger tips and finger valleys. The one or more fingers of the hand are labeled. One or more features for each finger of the hand are determined.