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.

Generally, the disclosed systems and methods implement improved detection of objects in three-dimensional (3D) space. More particularly, an improved 3D object detection system can exploit continuous fusion of multiple sensors and/or integrated geographic prior map data to enhance effectiveness and robustness of object detection in applications such as autonomous driving. In some implementations, geographic prior data (e.g., geometric ground and/or semantic road features) can be exploited to enhance three-dimensional object detection for autonomous vehicle applications. In some implementations, object detection systems and methods can be improved based on dynamic utilization of multiple sensor modalities. More particularly, an improved 3D object detection system can exploit both LIDAR systems and cameras to perform very accurate localization of objects within three-dimensional space relative to an autonomous vehicle. For example, multi-sensor fusion can be implemented via continuous convolutions to fuse image data samples and LIDAR feature maps at different levels of resolution.

A lane line detection method using a fusion network based on an attention mechanism, and a terminal device are provided. The method includes: synchronously acquiring natural images and point cloud data of a road surface; and inputting the natural images and the point cloud data into a pre-built and trained fusion network to output a lane line detection result. Time series frames and an attention mechanism are added to the fusion network to perform information fusing on the point cloud data and the natural images. Specifically, continuous frames are used to improve detection network performance to deal with complex situations such as label loss and vehicle being blocked; low-dimensional features are stitched with high-dimensional features by Skip Connection to make up for image detail information that is continuously lost as the network goes deeper, and the Decoder module is used to restore image dimensions to obtain a final result.

An apparatus and a method for controlling the output of driver information to a driver of a vehicle, with the objective of entertaining the driver and/or the passengers of the vehicle and/or increasing the driver attentiveness of the driver. A database of points of interest or objects of general interest, a database of topographic information, a device for determining the whereabouts of the vehicle, and an evaluation device to which these information items are delivered, are provided. The evaluation device ascertains, from the current whereabouts of the vehicle and from the topographic information, which points of interest or objects of general interest are present in the driver's field of view, and outputs via an output device the driver information regarding the point of interest or the object of general interest which has been ascertained by the evaluation device to be located in the driver's field of view.

The use of sensor data, data interactions between connected devices, data from physical world sensors and users of these where the data gathered is stored across central computation and storage servers, across multiple data nodes in secure and encrypted distributed ledgers, and the data is interacting with on-device computation and storage capabilities to create data interactive, electronic networks that enables multi-level control, variable access, payment and re-numeration capable, multi-user communications of real-time contextually relevant data, process and workflow data and information among network-connected devices, connected displays, sensors and the actions based on those communications, with the collected data gathered from the interactions stored on cloud based augmented intelligence computation servers and or select data stored in distributed ledger blockchain nodes with smart contract per data node delivering content, information, access and instructions based on past behavior and actions, instructions or computed commands with this data combined with the data of the outcome of these interactions stored on decentralized network of data nodes for immediate benefit, rewards, reoccurring remunerations, disclosure of information and benefits to authorized and approved users as the network-connected devices move from one location to another and/or the data/information flow among those devices change over time.

The present disclosure discloses a method and device for detecting a state of holding a steering wheel, wherein the method includes: a detection result is obtained by detecting a video stream collected from a target vehicle; an associated state of the first ROI information and the second ROI information in the two-dimensional plane carried in the detection result is obtained, wherein the first ROI information is ROI information about the steering wheel of the target vehicle, and the second ROI information is ROI information about the driver's hand of the target vehicle; a current state between the hand of the driver and the steering wheel of the target vehicle is determined according to the associated state. Then, the disclosure solves the technical problem in the related art that it is impossible to detect the grasping state of the steering wheel by the driver while driving.

The exemplary embodiments disclose a method, a computer program product, and a computer system for mitigating the risks associated with handling items. The exemplary embodiments may include collecting data relating to one or more items, extracting one or more features from the collected data, determining one or more hazards based on the extracted one or more features and one or more models, and displaying the one or more hazards within an augmented reality device worn by a user.

Systems and methods for identifying travel way features in real time are provided. A method can include receiving two-dimensional and three-dimensional data associated with the surrounding environment of a vehicle. The method can include providing the two-dimensional data as one or more input into a machine-learned segmentation model to output a two-dimensional segmentation. The method can include fusing the two-dimensional segmentation with the three-dimensional data to generate a three-dimensional segmentation. The method can include storing the three-dimensional segmentation in a classification database with data indicative of one or more previously generated three-dimensional segmentations. The method can include providing one or more datapoint sets from the classification database as one or more inputs into a machine-learned enhancing model to obtain an enhanced three-dimensional segmentation. And, the method can include identifying one or more travel way features based at least in part on the enhanced three-dimensional segmentation.

Disclosed is an electronic device. The electronic device includes a sensor unit that includes a first sensor and a second sensor, and a processor that is operatively connected with the sensor unit. The processor determines whether a given condition is satisfied, by using a first sensor signal of a user sensed by the first sensor, controls the first sensor to sense the first sensor signal every first cycle and controls the second sensor to sense a second sensor signal from the user every second cycle longer than the first cycle when the given condition is not satisfied, controls the second sensor to sense the second sensor signal every third cycle shorter than the second cycle when the given condition is satisfied, and recognize a gesture of the user by using the first sensor signal sensed every first cycle and the second sensor signal sensed every third cycle.

A system for performing remote artificial intelligence-assisted electronic warranty verification including at least one processor configured to transmit an instruction to capture at least one product image of a specific product, receive and perform product image analysis on the product image to identify at least one product-distinguishing characteristic, transmit an instruction to capture an image of a purchase receipt, receive and perform receipt image analysis on the purchase receipt image to identify product purchase information, access a universal data structure containing data on products offered by suppliers, use the at least one product-distinguishing characteristic and product purchase information to identify in the universal data structure the specific product, identify in the universal data structure a link to a warranty data structure of the supplier, access the link to lookup the specific product and receive a warranty coverage indication from the supplier data structure, and transmit an indication of warranty coverage.