568 results about "Confidence threshold" patented technology

Automated critical congenital heart defect (“CCHD”) screening systems and processes are described. A caregiver may be guided to use a single or dual sensor pulse oximeter to obtain pre- and post-ductal blood oxygenation measurements. A delta of the measurements indicates the possible existence or nonexistence of a CCHD. Errors in the measurements are reduced by a configurable measurement confidence threshold based on, for example, a perfusion index. Measurement data may be stored and retrieved from a remote data processing center for repeated screenings.

Automated critical congenital heart defect (“CCHD”) screening systems and processes are described. A caregiver may be guided to use a single or dual sensor pulse oximeter to obtain pre- and post-ductal blood oxygenation measurements. A delta of the measurements indicates the possible existence or nonexistence of a CCHD. Errors in the measurements are reduced by a configurable measurement confidence threshold based on, for example, a perfusion index. Measurement data may be stored and retrieved from a remote data processing center for repeated screenings.

A speech processing system that performs adaptations based upon non-sound external input, such as weather input. In the system, an acoustic environment can include a microphone and speaker. The microphone / speaker can receive / produce speech input / output to / from a speech processing system. An external input processor can receive non-sound input relating to the acoustic environment and to match the received input to a related profile. A setting adjustor can automatically adjust settings of the speech processing system based upon a profile based upon input processed by the external input processor. For example, the settings can include customized noise filtering algorithms, recognition confidence thresholds, output energy levels, and / or transducer gain settings.

The invention discloses an initiative study-based questioning and answering method and a questioning and answering system adopting the initiative study-based questioning and answering method, wherein the Initiative study-based questioning and answering method comprises the following steps of (1) performing question inputting; (2) performing pretreatment; (3) performing feature extraction; (4) performing question understanding; (5) performing judgment of confidence, a threshold value and credibility; (6) performing information retrieval and information processing; (7) performing answer extraction; (8) performing initiative study; (9) performing guide questioning according to the specific type of the question when the confidence is lower than the credibility, initiatively guiding a user to question without ambiguity and performing a new round of more effective questioning and answering. The questioning and answering system comprises five modules including a question inputting module, a pretreatment module, a semantics understanding module, an initiative study module and an answer outputting module.

Disclosed is a system and method for suggesting messages that are automatically learned, personalized and diversified by leveraging messages sent by a large number of users in order to provide message completions that are as engaging as possible. The disclosed systems and methods learn from recurrent messages sent to a recipient, and suggest message completions based upon user behavior. The systems and methods compute a ranked list of suggested message completions after every key stroke or character input, and if the list satisfies a given confidence threshold, it is returned and displayed to the user.

In one example, an apparatus includes a processor configured to extract a first set of one or more keypoints from a first set of blurred images of a first octave of a received image, calculate a first set of one or more descriptors for the first set of keypoints, receive a confidence value for a result produced by querying a feature descriptor database with the first set of descriptors, wherein the result comprises information describing an identity of an object in the received image, and extract a second set of one or more keypoints from a second set of blurred images of a second octave of the received image when the confidence value does not exceed a confidence threshold. In this manner, the processor may perform incremental feature descriptor extraction, which may improve computational efficiency of object recognition in digital images.

The invention discloses a method for the mixed customer services of intelligent robots and human beings. The method comprises the steps of S1, receiving the user information sent by a user terminal; S2, searching a database through triggering an intelligent robot based on the user information to obtain a search result; S3, judging whether the search result is correct or not based on an answer candidate method; on the condition that the search result is correct, returning the search result to the user terminal and getting back to the step S1; on the condition that the search result is not correct, triggering the human being-based service; giving a reply to a question based on the user information by the human being-based service and marking the replay as an effective answer; S4, recording the user information and the effective answer corresponding to the user information into the database by the intelligent robot. According to the technical scheme of the invention, questions are answered by the intelligent robot as much as possible. Meanwhile, based on a confident threshold, whether a question is forwarded to the human being-based service or not is intelligently judged. After the question is answered by the human being-based service, the intelligent robot automatically records the question and the answer into the database. Therefore, the self-learning of the intelligent robot database and the knowledge timely update are realized.

Embodiments of the present invention provide a voice identification method, which includes: obtaining voice data; obtaining a confidence value according to the voice data; obtaining a noise scenario according to the voice data; obtaining a confidence threshold corresponding to the noise scenario; and if the confidence value is greater than or equal to the confidence threshold, processing the voice data. An apparatus is also provided. The method and apparatus that flexibly adjust the confidence threshold according to the noise scenario greatly improve a voice identification rate under a noise environment.

A method and system for classification of endoscopic images is disclosed. An initial trained deep network classifier is used to classify endoscopic images and determine confidence scores for the endoscopic images. The confidence score for each endoscopic image classified by the initial trained deep network classifier is compared to a learned confidence threshold. For endoscopic images with confidence scores higher than the learned threshold value, the classification result from the initial trained deep network classifier is output. Endoscopic images with confidence scores lower than the learned confidence threshold are classified using a first specialized network classifier built on a feature space of the initial trained deep network classifier.

A method of defining data patterns for object handling includes obtaining an image of an input data area, processing the image to obtain image data, and comparing the image data with a pattern, wherein the pattern identifies spatial information of corresponding pattern fields of the pattern. The method further includes determining a confidence level of the comparison of the image data according to a success in matching the image data with the pattern fields, comparing the confidence level with a confidence threshold associated with the pattern, and selecting the pattern. A pattern output associated with the selected pattern is identified, wherein the pattern output corresponds to a canonical return format, and the pattern output is applied to the image data.

Systems and methods are provided for validating the authenticity of a signature on a document by providing a document from an account, the document including an actual signature and a machine-readable identifier, wherein the machine-readable identifier contains a string of data representing the integral characteristics of all valid account signatures and a person-specific confidence threshold. When the document is presented at a point of presentment, the document is scanned into a document-processing machine and the actual signature is compared against all valid account signatures.

A method for quickly identifying lanes-change condition of object vehicle includes utilizing machine vision and radar to collect horizontal and longitudinal distances, relative speed and the same lane possibility between object vehicle and local vehicle, making comparison and quantization on said data collected each time, making compensation and tracking prediction on relevant data, calculating confidence of each vehicle by using two layers of neural network training to obtain object vehicle weight and setting object vehicle to be dangerous object once calculated confidence coefficient is over confidence threshold.

Systems and methods are provided for validating the authenticity of a signature on a document by providing a document from an account, the document including an actual signature and a machine-readable identifier, wherein the machine-readable identifier contains a string of data representing the integral characteristics of all valid account signatures and a person-specific confidence threshold. When the document is presented at a point of presentment, the document is scanned into a document-processing machine and the actual signature is compared against all valid account signatures.

The present invention provides a neural network-based face detection model training method, a neural network-based face detection method, a neural network-based face detection model training system and a neural network-based face detection system. The training method includes the following steps that: the loss function of the bias network layer of a prediction face frame is calculated according to the bias information of the prediction face frame relative to a default face frame and the bias information of a real face frame relative to the default face frame; the loss function of the confidence network layer of the prediction face frame is calculated according to the confidence of the default face frame; the error of the two loss functions is calculated, and is fed back to a neural network, so that the weight of the neural network is adjusted; iterative training is repeated until convergence appears, so that a face detection model can be obtained, and therefore, the prediction face frame can contain a face more accurately. The detection method includes the following steps that: a face image to be detected is inputted to a trained face detection model, bias information and confidence are outputted; corresponding prediction face frames are calculated according to the bias information; and a prediction face frame corresponding to confidence greater than a preset confidence threshold or the highest confidence is selected as a face detection result.

The invention discloses an image recognition method and an image recognition device. According to one concrete embodiment, the method comprises the following steps of: obtaining an image to be recognized containing an object to be recognized; sending the image to be recognized to a server, and receiving a confidence degree parameter and marker information of a target object corresponding to the object to be recognized, wherein the confidence degree parameter and the marker information are returned by a server and are obtained through recognition on the image to be recognized; when the confidence degree parameter is greater than a confidence threshold, using the marker information of the target object as a recognition result; when the confidence degree parameter is smaller than the confidence degree threshold, obtaining marking information associated with the image to be recognized from a third party platform; and using the marking information as a recognition result. The image recognition method and the image recognition device have the advantages that the effect that the server automatic recognition and the third party marking information are combined is achieved; the recognition accuracy is improved; the third part marking information is used for training a recognition model corresponding to a machine learning recognition mode used by the server; and the training effect of the recognition model is improved.

This invention is an ultra-low frequency electromagnetic telemetry receiver which fuses multiple input receive sources to synthesize a decodable message packet from a noise corrupted telemetry message string. Each block of telemetry data to be sent to the surface receiver from a borehole tool is digitally encoded into a data packet prior to transmission. The data packet is modulated onto the ULF EM carrier wave and transmitted from the borehole to the surface and then are simultaneously detected by multiple receive sensors disbursed within the rig environment. The receive sensors include, but are not limited to, electric field and magnetic field sensors. The spacing of the surface receive elements is such that noise generators are unequally coupled to each receive element due to proximity and / or noise generator type (i.e. electric or magnetic field generators). The receiver utilizes a suite of decision metrics to reconstruct the original, non noise-corrupted data packet from the observation matrix via the estimation of individual data frames. The receiver will continue this estimation process until: 1) the message validates, or 2) a preset “confidence threshold” is reached whereby frames within the observation matrix are no longer “trusted”.

A method and apparatus for assisting a user in the dialing of a telephone call using voice nametags. A first step includes inputting a telephone number with text. The next steps automatically create a voice nametag from the text for each telephone number using grapheme-to-phoneme conversion. Upon initiation of dialing, a next step enters a spoken phrase, which is then compared to the stored voice nametags. A next step determines a confidence level score of a match between the spoken phrase data and the representations of the stored voice nametags against at least one threshold. A next step selects the stored voice nametag with the best match to the spoken phrase data. A next step provides feedback to the user dependent upon the confidence level of the match, which can include automatically dialing the call if the confidence level is high enough. As part of this last step, an audio feedback tag is generated and stored based on the recognition result passing a confidence threshold criterion. Further steps are provided for improving the audio quality of the stored nametag based on signal to noise ratio.

An interactive response system mixes HSR subsystems with ASR subsystems to facilitate overall capability of voice user interfaces. The system permits imperfect ASR subsystems to nonetheless relieve burden on HSR subsystems. An ASR proxy is used to implement an IVR system, and the proxy dynamically determines how many ASR and HSR subsystems are to perform recognition for any particular utterance, based on factors such as confidence thresholds of the ASRs and availability of human resources for HSRs.

A method of defining data patterns for object handling includes obtaining an image of an input data area, processing the image to obtain image data, and comparing the image data with a pattern, wherein the pattern identifies spatial information of corresponding pattern fields of the pattern. The method further includes determining a confidence level of the comparison of the image data according to a success in matching the image data with the pattern fields, comparing the confidence level with a confidence threshold associated with the pattern, and selecting the pattern. A pattern output associated with the selected pattern is identified, wherein the pattern output corresponds to a canonical return format, and the pattern output is applied to the image data.

Systems and methods are provided for validating the authenticity of a signature on a document by providing a document from an account, the document including an actual signature and a machine-readable identifier, wherein the machine-readable identifier contains a string of data representing the integral characteristics of all valid account signatures and a person-specific confidence threshold. When the document is presented at a point of presentment, the document is scanned into a document-processing machine and the actual signature is compared against all valid account signatures.

This invention is an ultra-low frequency electromagnetic telemetry receiver which fuses multiple input receive sources to synthesize a decodable message packet from a noise corrupted telemetry message string. Each block of telemetry data to be sent to the surface receiver from a borehole tool is digitally encoded into a data packet prior to transmission. The data packet is modulated onto the ULF EM carrier wave and transmitted from the borehole to the surface and then are simultaneously detected by multiple receive sensors disbursed within the rig environment. The receive sensors include, but are not limited to, electric field and magnetic field sensors. The spacing of the surface receive elements is such that noise generators are unequally coupled to each receive element due to proximity and / or noise generator type (i.e. electric or magnetic field generators). The receiver utilizes a suite of decision metrics to reconstruct the original, non noise-corrupted data packet from the observation matrix via the estimation of individual data frames. The receiver will continue this estimation process until: 1) the message validates, or 2) a preset “confidence threshold” is reached whereby frames within the observation matrix are no longer “trusted”.

An autonomous vehicle may be operable in an autonomous mode and a manual mode. A confidence threshold is accessed from a database. The confidence threshold may be associated with a particular geographic area containing the autonomous vehicle. The confidence threshold may be constant for the geographic area accessible by the autonomous vehicle. A computing device calculates a vehicle confidence level based on at least one confidence factor and compares the confidence threshold to the vehicle confidence level. The computing device generates a driving mode command for a vehicle based on the comparison. In one example, the driving mode command transitions the autonomous vehicle to the autonomous mode, if applicable, when the vehicle confidence score exceeds the confidence threshold. In one example, the driving mode command transitions the autonomous vehicle to the manual mode, if applicable, when the vehicle confidence score does not exceed the confidence threshold.

A system for processing images captured in a retail store is provided. The system may include a processor configured to: access a database storing a group of product models; receive an image depicting at least part of a store shelf having a plurality of products of a same type displayed thereon; analyze the image and determine a first candidate type of the products based on the group of product models and the image analysis; determine a first confidence level associated with the first candidate type; when the first confidence level is below a confidence threshold, determine a second candidate type of the products using contextual information; determine a second confidence level associated with the determined second candidate type of the plurality of products; and when the second confidence level is above the confidence threshold, initiate an action to update the group of product models stored in the database.

Spatial crowdsourcing systems and methods assign spatial tasks to be performed by human workers. The systems and methods can verify the validity of the results provided by workers. Every worker can have a reputation score stating the probability that the worker performs a task correctly. Every spatial task can have a confidence threshold determining the minimum quality of the accepted level of its result. To satisfy this threshold, a task may be assigned redundantly to multiple workers. A reputation score can be associated to every worker, which represents the probability that a worker performs a task correctly. A task may be assigned to a subset of workers whose aggregate reputation score satisfies the confidence of the task.

A method and system for training a special object detector to distinguish a foreground object appearing in a sequence of frames for a target domain. The sequence of frames depicts motion of the foreground object in a non-uniform background. The foreground object is detected in a high-confidence subwindow of an initial frame of the sequence, which includes computing a measure of confidence that the high-confidence subwindow includes the foreground object and determining that the measure of confidence exceeds a specified confidence threshold. The foreground object is tracked in respective positive subwindows of subsequent frames appearing after the initial frame. The subsequent frames are within a specified short period of time. The positive subwindows are used to train the special object detector to detect the foreground object in the target domain. The positive subwindows include the subwindow of the initial frame and the respective subwindows of the subsequent frames.

A method is provided of a bank processing a check in an automatic signature verification system. The method comprises receiving a check image having a payor's signature, extracting the payor's signature from the check image, comparing the extracted payor's signature with a reference signature, providing a confidence value based upon the comparison of the extracted payor's signature with the reference signature, selecting one of a plurality of confidence threshold values based upon amount of the check, and comparing the confidence value with the selected confidence threshold value to determine if payment of the check amount is approved.

The embodiment of the invention provides a voice identification method which comprises the following steps of: acquiring voice data; acquiring a first confidence level value according to the voice data; acquiring a noise scene according to the voice data; acquiring a second confidence level value corresponding to the noise scene according to the first confidence level value; and if the second confidence level value is greater than or equal to a pre-stored confidence level threshold value, processing the voice data. The invention also discloses a device. According to the noise scene, the method and the device can be used for flexibly adjusting the confidence level value, so that the voice identification rate in the noise environment is greatly improved.