1144results about "Matching and classification" patented technology

The present disclosure generally relates to enrolling a biometric feature for use with a peripheral device. While a computer system is connected to an external device, the computer system receives a first request to enroll a biometric feature. In response to receiving the request and in accordance with a determination that the request satisfies a first set of one or more criteria, the computer system displays a user interface object prompting a user to provide an authorization input to one or more input devices physically connected to the computer system. While displaying the first user interface object, the computer system receives user input. In response to receiving the user input and in accordance with a determination that the user input includes the authentication input, the computer system initiates a process to enroll the biometric feature using a biometric sensor that is integrated with the external device.

This disclosure describes a user-recognition system that may perform one or more verification methods upon identifying a previous image that matches a current image of a palm of a user. For instance, the user-recognition system may perform the verification method(s) as part of the recognition method (e.g., after recognizing a matching image), in response to an audit process, in response to a request to re-analyze the image data (e.g., because a user indicates that he or she was not associated with a particular purchase or shopping session), and / or the like.

Systems and methods for tokenless authorization are provided. Obtaining an electronic representation of an initial biometric sampling of a registrant. Applying the initial electronic representation to a first cryptographic function that produces a unique digital identifier (UDI). Obtaining account information constructs corresponding to an account by the registrant with a third party. Generating a unique secure identification number (SIN) using the UDI and the account information constructs. Storing a unique link from the UDI to the account information constructs. Receiving a request for service and an electronic representation of a second biometric sampling. Forming the UDI by applying the second electronic representation to the first cryptographic function. Verifying the UDI corresponds to the stored UDI to reconstruct the unique SIN from the UDI and using this unique SIN to retrieve the account information constructs through the indexed data structure. Transmitting the request and the unique SIN to the third party.

Disclosed in the embodiments of the present application are service processing methods, an apparatus, a device, a storage medium and a program product. A method comprises: receiving subject description information sent by a biological recognition apparatus, the subject description information comprising biological features and position information of a target subject; acquiring identity information of the target subject recorded in the biological features, and acquiring a service information set configured in association with the identity information; screening out from the service information set at least one piece of candidate service information matched with the position information; sending the at least one piece of candidate service information to a terminal device associated with the identity information, and in response to a selection operation triggered by the target subject, the terminal device determining at least one piece of target service information from amongst the at least one piece of candidate service information; and receiving the at least one piece of target service information returned by the terminal device, and processing a service corresponding to each piece of target service information amongst the at least one piece of target service information.

Systems herein describe a secured transaction system for accessing a camera stream from a front-facing camera unit of a wearable computing device, identifying a visual marker in the camera feed associated with a payment application, in response to identifying the visual marker, transmitting a request to an operating system of the wearable computing device to isolate access of the camera stream to the payment application and in response to transmitting the request, initiating a transaction using the payment application.

The invention relates to the technical field of building design, and discloses an Internet-based building design dynamic process management system, which comprises a multi-factor identity verification module, a distributed data storage module, a process dynamic optimization engine, a behavior evaluation and intervention module and an intelligent audit tracking system. According to the building design dynamic process management system based on the Internet, through cooperative work of the process dynamic optimization engine and the behavior evaluation and intervention module, the problem that task optimization of a traditional process management system depends on a preset rule is solved; the flow dynamic optimization engine dynamically adjusts the task priority and resource allocation by using an improved ant colony algorithm based on the real-time task progress and the executor behavior data; meanwhile, the behavior evaluation and intervention module quantitatively evaluates the behavior of the executor according to a weighted scoring model, triggers an automatic intervention process when necessary, and can quickly adapt to sudden changes, so that the resource allocation efficiency is improved, and human errors are reduced.

Methods and systems are described for identity verification and deepfake prevention. A first video of a person is captured during an in-person interaction, the person's identity is verified, and the video is associated with the verified identity. In a subsequent electronic interaction, information about a second person is accessed, a second video of the second person is captured, and a trained neural network model is used to determine if the second person is attempting to identify as the first person. If the second person is not attempting to identify as the first person, the electronic interaction proceeds. If the second person is attempting to identify as the first person, the model determines if the first person is likely the same as the second person, transmitting a positive indicator if likely the same, and a negative indicator if not. Related networks, models, apparatuses, devices, techniques, and articles are also described.

An enhanced lifeform transmission system to locate a lifeform (e.g., human, animal, etc.) wanting to be identified as a lifeform for collision avoidance. The lifeform transceiver is worn on a limb or neck of the lifeform. The collision avoidance system is housed inside the vehicle and receives communications from the lifeform transceiver. The lifeform is automatically detected and the lifeform transmitter is automatically turned on and off when a lifeform enters and exits a vehicle. The lifeform transceiver also tracks and protects the lifeform in a manufacturing facility or at an outdoor location.

In various examples, infrared image data may be used to detect a subcutaneous characteristic(s) (e.g., a palm vein topology) of a person (e.g., a person requesting entry to a vehicle, a vehicle occupant) and authenticate the user based on the detected subcutaneous characteristic(s). For example, infrared image data representing one or more acquired subcutaneous characteristics (e.g., a topology of veins and / or other blood vessels in a region of the authenticating user's palm, hand, neck, forearm, face, fingertip, eye, etc.) may be generated. Hand and / or palm detection may be applied to detect a region depicting the user's hand or palm, and that region (or some subset thereof) may be segmented to generate a representation of an acquired vein topology. The acquired vein topology may be compared with one or more reference vein topologies stored in a database to determine whether the acquired vein topology matches one of the reference vein topologies.

The invention relates to the technical field of vulnerability detection, in particular to an industrial asset fingerprint identification-based vulnerability stain detection system, which comprises a data acquisition module, a data analysis module, a fingerprint identification module, a vulnerability matching module, a stain analysis module and a verification module. The flow data of each industrial asset device in operation is collected in real time to generate fingerprint information of the industrial asset device, the data collected in real time is matched with a vulnerability library according to the fingerprint information, existing known vulnerabilities are identified, and possible taint propagation paths are deduced according to network topology and taint sources by constructing a network topological graph, so that the taint propagation efficiency is improved. The method comprises the following steps: identifying affected equipment, evaluating the flow change of the affected equipment, calculating the influence degree of a taint source on a network, identifying abnormal activities in a taint propagation process, evaluating the network security risk, and adjusting a monitoring strategy and a threshold value in time according to an evaluation result to ensure the accuracy and reliability of a monitoring system.

This invention is directed to an electronic device with an embedded authentication system for restricting access to device resources. The authentication system may include one or more sensors operative to detect biometric information of a user, The sensors may be positioned in the device such that the sensors may detect appropriate biometric information as the user operates the device, without requiring the user to perform a step for providing the biometric information (e.g., embedding a fingerprint sensor in an input mechanism instead of providing a fingerprint sensor in a separate part of the device housing). In some embodiments, the authentication system may be operative to detect a visual or temporal pattern of inputs to authenticate a user. In response to authenticating, a user may access restricted files, applications (e.g., applications purchased by the user), or settings (e.g., application settings such as contacts or saved game profile).

Provided is an electronic device. The electronic device may include a display, a fingerprint sensor provided in an area of the display, and at least one processor. The at least one processor may receive a user input for fingerprint registration, based on the user input, control the display to display a first user interface displaying information to guide a position for a touch input based on a position of the fingerprint sensor at a first position on the display, and based on receiving a first touch on the first user interface, control the display to display a second user interface indicating a degree of a fingerprint recognition related to the first touch.

A multi-port interface device for connecting multiple computing devices for data and power transfer includes a housing with an internal power source. A processor is electrically coupled to the internal power source. A power input port electrically coupled to the internal power source is designed to receive a power cord. The power cord is electrically couplable to an extrinsic power source to transfer power from the extrinsic power source to the internal power source. A plurality of ports electrically coupled to the processor is inset into the housing. Each port of the plurality of ports is exposed within the housing. The plurality of ports includes a plurality of universal serial bus ports and a memory card port.

Embodiments of the present application provide a fingerprint anti-counterfeiting neural network training method, a fingerprint anti-counterfeiting method and device, comprising: obtaining multiple sets of training data, each set of training data including: first native domain data, second native domain data and third native domain data; using the multiple sets of training data to train an initial classification network to obtain a target classification network, the initial classification network including a fusion subnetwork and a classification subnetwork, for each set of training data, the fusion subnetwork is used to generate a first fingerprint matching pair based on the feature description matrix of the first native domain data and the second native domain data, and generate a second fingerprint matching pair based on the feature description matrix of the first native domain data and the third native domain data, and the classification subnetwork is used for fingerprint classification and identification based on the first fingerprint matching pair and the second fingerprint matching pair. Through the present application, the problem of low identification accuracy of true and false fingerprints in related technologies is solved, and the effect of improving the identification accuracy of true and false fingerprints is achieved.

A fingerprint sensing system. The fingerprint sensing system includes: at least one sensor; at least one display device; at least one application processor; and at least one secure enclave processor. The application processor(s) receives fingerprint data from the sensor(s) and provides the fingerprint data to the secure enclave processor(s). The secure enclave processor(s) decodes the fingerprint data and provides a signal indicative of at least one matched node. The application processor(s), responsive to receipt of the signal indicative of the matched node(s), presents at least a portion of a synthetic fingerprint image via at least one display device corresponding to the matched node(s).

An apparatus includes a memory and a processor. The memory stores biometric data obtained from an account holder at a first location and identification information provided by the account holder that was used to open an existing account at the first location. The processor receives, from a device, data corresponding to an applicant that includes biometric data obtained from the applicant at a second location and identification information provided by the applicant at the second location. The applicant is requesting to open a new account using the identification information at the second location. In response to receiving the applicant's data, the processor determines that the applicant's biometric data matches the account holder's biometric data. The processor also determines that the applicant's identification information does not match the account holder's identification information. In response, the processor transmits an alert to the device indicating that the applicant's identity could not be verified.

A system to generate an image classifier and test it nearly instantaneously is described herein. Image embeddings generated by an image fingerprinting model are indexed and an associated approximate nearest neighbors (ANN) model is generated. The embeddings in the index are clustered and the clusters are labeled. Users can provide just a few images to add to the index as a labeled cluster. The ANN model is trained to receive an image embedding as input and return a score and label of the most similar identified embedding. The label may be applied if the score exceeds a threshold value. The image classifier can be tested efficiently using Leave One Out Cross Validation (“LOOCV”) to provide near-instantaneous quality indications of the image classifier to the user. Near-instantaneous indications of outliers in the provided images can also be provided to the user using a distance to the centroid calculation.

Object description information that is transmitted by a biometric recognition apparatus is received, the object description information includes a biometric feature of a target object and location information of the target object. Identity information of the target object is obtained according to the biometric feature. A service information set in association with the identity information is obtained. From the service information set, one or more pieces of candidate service information are selected. The one or more pieces of candidate service information are transmitted to a terminal device associated with the identity information. At least a first piece of target service information returned by the terminal device is received. At least a first service corresponding to the first piece of target service information is processed. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.

An authentication system comprises a storage device for storing biometric features, an imaging device for capturing a biometric feature, an image correction unit for converting the image quality of the image captured by the imaging device, and an authentication processing unit. The image correction unit generates an image before color correction of one or more images in which biometrics is captured and transforms the pre-color correction image by a plurality of values within a predetermined search range for color information to generate a plurality of color information transformed images. The image correction unit searches the color information conversion image that best represents the biometric feature for each biometric feature as the optimal color information for each biometric feature from the plurality of color information conversion images.

The invention relates to a fingerprint lock dynamic encryption authentication method and system and a medium. The method comprises a registration stage and an authentication stage. Wherein in the registration stage, lock body environment real-time physical parameters are collected, and a dynamic environment secret key is generated through a chaotic mapping function; acquiring a user fingerprint, identifying core and non-core feature regions, and encrypting the two types of regions by combining a dynamic environment key and a user key to generate registration encrypted fingerprint data; and dividing the data into two data fragments by using a quantum noise source true random sequence, storing the first data fragment in a local security chip, and encrypting the second data fragment and storing the encrypted second data fragment in a cloud server. In the authentication stage, environment parameters are collected in real time to generate a verification key, and the verification key is compared with a registration key; and when the two fragments are consistent, recombining the two fragments to restore the encrypted fingerprint data, authenticating the fingerprint input by the user, unlocking if the authentication succeeds, and triggering risk grading processing if the continuous failure reaches a threshold value. The overall safety and reliability of the fingerprint lock system are improved.

The invention provides a fingerprint signal processing method and device and electronic equipment, and can be applied to the technical field of fingerprint identification. Based on the method, before specific implementation, fingerprint pixel units in a fingerprint pixel unit array circuit can be connected with a preset gain amplifier with adjustable gain, and an improved fingerprint pixel unit array circuit is obtained. In specific implementation, when a fingerprint related signal is received, a matched target convolution kernel is determined in the fingerprint pixel unit array circuit; wherein the range of the target convolution kernel comprises a plurality of fingerprint pixel units; and traversing the fingerprint pixel unit array circuit by using a target convolution kernel, and processing the fingerprint related signal to obtain a target fingerprint signal. Therefore, the fingerprint pixel units in the fingerprint pixel unit array circuit can be fully utilized, the received fingerprint related signals are processed by constructing and using the corresponding target convolution kernels, the signal-to-noise ratio of the signals is effectively improved, and target fingerprint signals with high quality are obtained.

A medical imaging system including an optical identifier camera for imaging a medical device, a medical device packaging, a patient, or a technician. The system further includes an imaging probe for imaging of a target location, and a console with optical identifier logic to extract identifier markers or characteristics from the image of the medical device, packaging, patient or technician. A parameter logic determines the medical imaging parameters based on the identifiers or characteristics, and a medical imaging logic captures medical images of the medical device. The system enables efficient and accurate imaging of medical devices on the specific patient, by a specific technician, enhancing diagnostic capabilities and treatment planning in medical parameters.

A detection device includes a plurality of optical sensors arranged in a detection area, a light source configured to emit light that is emitted to an object to be detected and is detected by the optical sensors, and a processor configured to perform processing based on outputs from the optical sensors. The processor is configured to determine, based on the outputs of the respective optical sensors obtained at a cycle of a predetermined period, an optical sensor an output of which is to be employed from among the optical sensors.

A fingerprint recognition method and apparatus are provided. The method is applied to the field of fingerprint recognition technologies. The method includes: when a first fingerprint image is successfully matched, judging whether matching information of the first fingerprint image satisfies a first preset condition; when the matching information of the first fingerprint image satisfies the first preset condition, judging whether a cumulative update count of a second fingerprint template is greater than a first quantity threshold; when the cumulative update count of the second fingerprint template is greater than the first quantity threshold, judging whether priority information of the second fingerprint template satisfies a second preset condition; and when the priority information of the second fingerprint template satisfies the second preset condition, updating the second fingerprint template with the first fingerprint image. A high-quality fingerprint image is selected through a plurality of judgment conditions to update a fingerprint template library. Matching is performed based on an updated fingerprint template library. This can increase a fingerprint unlocking rate and an unlocking speed, so that user experience in unlocking is improved.

A computer-implemented method of locally verifying an attribute associated with a user is disclosed. The method comprises performing, by a computing device, steps including: capturing biometric verification data using the computing device; determining whether the biometric verification data corresponds to the user by comparing the biometric verification data with authenticated biometric data of the user previously obtained from an identity document, ID, and stored locally on the computing device; and in response to determining that the biometric verification data corresponds to the user, verifying the attribute associated with the user based on attribute information associated with the user previously obtained from the ID and stored locally on the computing device.

Hierarchical patch-wise diffusion models (HPDMs) use a diffusion paradigm that learns a hierarchical distribution of patches instead of whole videos for efficient patch-wise training of diffusion models. To enforce consistency between the patches, deep context fusion may be used to propagate the context information from low-scale to high-scale patches in a hierarchical manner. To accelerate patch-wise training and inference, adaptive computation also may be used to allocate more computational resources and network capacity towards coarse image details and to cheapen synthesis of high-frequency texture details. All the processing stages are jointly trained to provide spatially aligned global context to the higher levels of the cascade. As a result, the model does not operate on the full-resolution inputs, which allows the model to be trained on high-resolution video datasets in an end-to-end fashion.

Embodiments of this application disclose a palm print recognition method, a method for training a feature extraction model, a device, and a storage medium, and belong to the field of computer technologies. The method includes: obtaining sample hand images for each of a plurality of sample user identifiers, at least two of the sample hand images associated with the each of the plurality of sample user identifier being acquired from image acquisition devices having different image acquisition characteristics; calling a feature extraction model to extract sample palm print features of the plurality of sample user identifiers; and adjusting the feature extraction model according to the sample palm print features of the plurality of sample user identifiers.

The present disclosure provides an artificial intelligence-infected asymptomatic people movement-tracing apparatus and a method which in an emergency such as an epidemic pandemic, use an artificial intelligence movement-tracing apparatus of infected asymptomatic people of the present disclosure which is personally installed in the residence of the tracing target to automatically check whether to match the traffic line of the tracing target and the traffic line of the confirmed case and automatically report to the disease control authority only when the traffic lines match to protect individual privacy compared to the centralized system and automatically search for infected asymptomatic people classified as blind confirmed cases (hidden positive people) and self-quarantine subjects to quickly establish an infectious disease management system for suspected disease patients and efficiently manage the people from the spread of infectious diseases.

A driver monitoring (DM) computing device for monitoring driving behavior of a driver in real-time is provided. The DM computing device detects a user computer device associated with a driver inside the vehicle. The DM computing device collects state data of the user computer device. The state data includes data as to a state of the user computer device during a currently occurring trip. The DM computing device collects vehicle operation data of the vehicle while the driver and the user computer device are inside the vehicle. The DM computing device compares the collected vehicle operation data and the state data of the user computer device to determine whether the user computer device was activated during the currently occurring trip. The DM computing device causes a driving reward to be applied to an account associated with the driver for inactivity of the user computer device during the currently occurring trip.

A fingerprint recognition method and apparatus are provided. The method is applied to the field of fingerprint recognition technologies. The method includes: when a first fingerprint image is successfully matched, judging whether matching information of the first fingerprint image satisfies a first preset condition; when the matching information of the first fingerprint image satisfies the first preset condition, judging whether a cumulative update count of a second fingerprint template is greater than a first quantity threshold; when the cumulative update count of the second fingerprint template is greater than the first quantity threshold, judging whether priority information of the second fingerprint template satisfies a second preset condition; and when the priority information of the second fingerprint template satisfies the second preset condition, updating the second fingerprint template with the first fingerprint image. A high-quality fingerprint image is selected through a plurality of judgment conditions to update a fingerprint template library. Matching is performed based on an updated fingerprint template library. This can increase a fingerprint unlocking rate and an unlocking speed, so that user experience in unlocking is improved.