1228 results about "Pattern identification" patented technology

A flow processing facility, which uses a set of artificial neurons for pattern recognition, such as a self-organizing map, in order to provide security and protection to a computer or computer system supports unified threat management based at least in part on patterns relevant to a variety of types of threats that relate to computer systems, including computer networks. Flow processing for switching, security, and other network applications, including a facility that processes a data flow to address patterns relevant to a variety of conditions are directed at internal network security, virtualization, and web connection security. A flow processing facility for inspecting payloads of network traffic packets detects security threats and intrusions across accessible layers of the IP-stack by applying content matching and behavioral anomaly detection techniques based on regular expression matching and self-organizing maps. Exposing threats and intrusions within packet payload at or near real-time rates enhances network security from both external and internal sources while ensuring security policy is rigorously applied to data and system resources. Intrusion Detection and Protection (IDP) is provided by a flow processing facility that processes a data flow to address patterns relevant to a variety of types of network and data integrity threats that relate to computer systems, including computer networks.

An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation which may be efficiently processed to determine correspondence. Applications of the interface and system include a VCR, medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation which may be efficiently processed to determine correspondence. Applications of the interface and system include a VCR, medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

A method and system for direct audio capture and identification of the captured audio. A user may then be offered the opportunity to purchase recordings directly over the Internet or similar outlet. The system preferably includes one or more user-carried portable audio capture devices that employ a microphone, analog to digital converter, signal processor, and memory to store samples of ambient audio or audio features calculated from the audio. Users activate their capture devices when they hear a recording that they would like to identify or purchase. Later, the user may connect the capture device to a personal computer to transfer the audio samples or audio feature samples to an Internet site for identification. The Internet site preferably uses automatic pattern recognition techniques to identify the captured samples from a library of recordings offered for sale. The user can then verify that the sample is from the desired recording and place an order online. The pattern recognition process uses features of the audio itself and does not require the presence of artificial codes or watermarks. Audio to be identified can be from any source, including radio and television broadcasts or recordings that are played locally.

A method and system for direct audio capture and identification of the captured audio. A user may then be offered the opportunity to purchase recordings directly over the Internet or similar outlet. The system preferably includes one or more user-carried portable audio capture devices that employ a microphone, analog to digital converter, signal processor, and memory to store samples of ambient audio or audio features calculated from the audio. Users activate their capture devices when they hear a recording that they would like to identify or purchase. Later, the user may connect the capture device to a personal computer to transfer the audio samples or audio feature samples to an Internet site for identification. The Internet site preferably uses automatic pattern recognition techniques to identify the captured samples from a library of recordings offered for sale. The user can then verify that the sample is from the desired recording and place an order online. The pattern recognition process uses features of the audio itself and does not require the presence of artificial codes or watermarks. Audio to be identified can be from any source, including radio and television broadcasts or recordings that are played locally.

An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation which may be efficiently processed to determine correspondence. Applications of the interface and system include a VCR, medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

A system for wirelessly locating mobile station / units (MS) and using resulting location determinations for providing a product or service is disclosed. The system is useful for routing an MS user to a plurality of desired locations, alerting an MS user to a nearby desired product or service based on satisfaction of user criteria, and providing enhanced security and 911 response. In one embodiment, the system responds to MS location requests via, e.g., Internet communication between a distributed network of location processing sites. A plurality of locating technologies including those based on: (1) TDOA; (2) pattern recognition; (3) timing advance; (5) GPS and network assisted GPS, (6) angle of arrival, (7) super resolution enhancements, and (8) supplemental information from low cost base stations can be activated, in various combinations, by system embodiments. MS location difficulties resulting from poor location accuracy / reliability and / or poor coverage are alleviated via such technologies in combination with automatically adapting and calibrating system performance according to environmental and geographical changes so that the system becomes progressively more comprehensive and accurate. Further, the system can be modularly configured for use in location signaling environments ranging from urban, dense urban, suburban, rural, mountain to low traffic or isolated roadways. Accordingly, the system is useful for 911 emergency calls, tracking, routing, people and animal location including applications for confinement to and exclusion from certain areas.

A system is disclosed for selectively applying a paraphrase alternation pattern to a textual input. The system includes a pattern identification component for processing a collection of data and identifying a plurality of potentially applicable paraphrase alternation patterns. A context model provides an objective frame of reference in which to compare one or more of the plurality of potentially applicable paraphrase alternation patterns to the textual input to determine whether the pattern can be applied without changing meaning. A language model provides a principled basis for determining the boundaries of the text segment to be modified.

In a hierarchical neural network having a module structure, learning necessary for detection of a new feature class is executed by a processing module which has not finished learning yet and includes a plurality of neurons which should learn an unlearned feature class and have an undetermined receptor field structure by presenting a predetermined pattern to a data input layer. Thus, a feature class necessary for subject recognition can be learned automatically and efficiently.

A system for wirelessly locating mobile station / units (MS) and using resulting location determinations for providing a product or service is disclosed. The system is useful for routing an MS user to a plurality of desired locations, alerting an MS user to a nearby desired product or service based on satisfaction of user criteria, and providing enhanced security and 911 response. In one embodiment, the system responds to MS location requests via, e.g., Internet communication between a distributed network of location processing sites. A plurality of locating technologies including those based on: (1) TDOA; (2) pattern recognition; (3) timing advance; (5) GPS and network assisted GPS, (6) angle of arrival, (7) super resolution enhancements, and (8) supplemental information from low cost base stations can be activated, in various combinations, by system embodiments. MS location difficulties resulting from poor location accuracy / reliability and / or poor coverage are alleviated via such technologies in combination with automatically adapting and calibrating system performance according to environmental and geographical changes so that the system becomes progressively more comprehensive and accurate. Further, the system can be modularly configured for use in location signaling environments ranging from urban, dense urban, suburban, rural, mountain to low traffic or isolated roadways. Accordingly, the system is useful for 911 emergency calls, tracking, routing, people and animal location including applications for confinement to and exclusion from certain areas.

Apparatus and methods are provided for use with a subject who is undergoing respiration. A motion sensor senses motion of a subject. A breathing pattern analysis unit analyzes components of the sensed motion that result from the subject's respiration. The breathing pattern analysis unit includes double-movement-respiration-cycle-pattern-identification functionality that designates respiration cycles as being double-movement-respiration-cycles (DMRC's) by determining that the cycles define two subcycles. Double-movement-respiration-cycle-event-identification functionality of the breathing pattern analysis unit identifies a DMRC event by detecting that the subject has undergone a plurality of DMRC's. An output is generated that is indicative of the subject having used accessory muscles in breathing, in response to identification of the double-movement-respiration-cycle event. Other embodiments are also described.

A system and method used to assess animal behavior includes a module having sensors that collects a variety of physical and biological data from a test subject. Interpretation of the data is provided to assess the test subject's behavior, neurology, biochemistry and physiology. The module is useful in observing the effects of a drug on the test animal and providing information on the drug's signature. Another advantage is the module's portability that allows it to be used in standard laboratory cages. This portability allows the animal to be tested in its own habitat, that can reduce any erroneous data due to stressing the animal when removed to a test cage. Additionally, the module's design allows for parallel data collection and interpretation from several laboratory animals undergoing different experiments. Multi-dimensional modeling of the test subject based the system's interpretation of the data allows pattern recognition of the drug signature, and predictive drug analysis.

A system and method in accordance with the present invention determines in real-time the portions of a set of characters from a data or character stream which satisfies one or more predetermined regular expressions. A Real-time Deterministic Finite state Automaton (RDFA) ensures that the set of characters is processed at high speeds with relatively small memory requirements. An optimized state machine models the regular expression(s) and state related alphabet lookup and next state tables are generated. Characters from the data stream are processed in parallel using the alphabet lookup and next state tables, to determine whether to transition to a next state or a terminal state, until the regular expression is satisfied or processing is terminated. Additional means may be implemented to determine a next action from satisfaction of the regular expression.

A computer automated method that applies supervised pattern recognition to classify whether voxels in a medical image data set correspond to a tissue type of interest is described. The method comprises a user identifying examples of voxels which correspond to the tissue type of interest and examples of voxels which do not. Characterizing parameters, such as voxel value, local averages and local standard deviations of voxel value are then computed for the identified example voxels. From these characterizing parameters, one or more distinguishing parameters are identified. The distinguishing parameter are those parameters having values which depend on whether or not the voxel with which they are associated corresponds to the tissue type of interest. The distinguishing parameters are then computed for other voxels in the medical image data set, and these voxels are classified on the basis of the value of their distinguishing parameters. The approach allows tissue types which differ only slightly to be distinguished according to a user's wishes.

A system for wirelessly locating mobile station / units (MS) and using resulting location determinations for providing a product or service is disclosed. The system is useful for routing an MS user to a plurality of desired locations, alerting an MS user to a nearby desired product or service based on satisfaction of user criteria, and providing enhanced security and 911 response. In one embodiment, the system responds to MS location requests via, e.g., Internet communication between a distributed network of location processing sites. A plurality of locating technologies including those based on: (1) TDOA; (2) pattern recognition; (3) timing advance; (5) GPS and network assisted GPS, (6) angle of arrival, (7) super resolution enhancements, and (8) supplemental information from low cost base stations can be activated, in various combinations, by system embodiments. MS location difficulties resulting from poor location accuracy / reliability and / or poor coverage are alleviated via such technologies in combination with automatically adapting and calibrating system performance according to environmental and geographical changes so that the system becomes progressively more comprehensive and accurate. Further, the system can be modularly configured for use in location signaling environments ranging from urban, dense urban, suburban, rural, mountain to low traffic or isolated roadways. Accordingly, the system is useful for 911 emergency calls, tracking, routing, people and animal location including applications for confinement to and exclusion from certain areas.

The present invention is based on the encoding of sequential data or sequences in a novel manner that permits efficient storage and processing of sequential data, as well as methods for searching sequences or databases of sequences. The methods and systems of the current invention may be adapted broadly to various fields of application and to a variety of sequences types. For example, the current invention has broad application including to the fields of bioinformatics, molecular biology, pharmacogenomics, phonetic sequences, lexicographic sequences, signal analysis, game playing, law enforcement, biometrics, medical diagnosis, equipment maintenance and micro-array data analysis.

A computer-implemented pattern recognition method, system and program product, the method comprising in one embodiment: creating electronically a linkage between a plurality of models within a classifier module within a pattern recognition system such that any one of said plurality of models may be selected as an active model in a recognition process; creating electronically a null hypothesis between at least one model of said plurality of linked models and at least a second model among said plurality of linked models; accumulating electronically evidence to accept or reject said null hypothesis until sufficient evidence is accumulated to reject said null hypothesis in favor of one of said plurality of linked models or until a stopping criterion is met; and transmitting at least a portion of the electronically accumulated evidence or a summary thereof to accept or reject said null hypothesis to a pattern classifier module.

A system for wirelessly locating mobile station / units (MS) and using resulting location determinations for providing a product or service is disclosed. The system is useful for routing an MS user to a plurality of desired locations, alerting an MS user to a nearby desired product or service based on satisfaction of user criteria, and providing enhanced security and 911 response. In one embodiment, the system responds to MS location requests via, e.g., Internet communication between a distributed network of location processing sites. A plurality of locating technologies including those based on: (1) TDOA; (2) pattern recognition; (3) timing advance; (5) GPS and network assisted GPS, (6) angle of arrival, (7) super resolution enhancements, and (8) supplemental information from low cost base stations can be activated, in various combinations, by system embodiments. MS location difficulties resulting from poor location accuracy / reliability and / or poor coverage are alleviated via such technologies in combination with automatically adapting and calibrating system performance according to environmental and geographical changes so that the system becomes progressively more comprehensive and accurate. Further, the system can be modularly configured for use in location signaling environments ranging from urban, dense urban, suburban, rural, mountain to low traffic or isolated roadways. Accordingly, the system is useful for 911 emergency calls, tracking, routing, people and animal location including applications for confinement to and exclusion from certain areas.

An adequate solution for computer vision applications is arrived at more efficiently and, with more automation, enables users with limited or no special image processing and pattern recognition knowledge to create reliable vision systems for their applications. Computer rendering of CAD models is used to automate the dataset acquisition process and labeling process. In order to speed up the training data preparation while maintaining the data quality, a number of processed samples are generated from one or a few seed images.

The invention relates to an anomaly detection method based on a motion field local statistical character analysis. The system mainly comprises the motion field analysis of video images, a local statistical character extraction and a statistical study and a mode identification technology based on samples. Firstly, the characteristics of objects in an image are extracted through a basic motion analyzing technology, the motion status is calculated, and a motion field is formed. On the basis, the statistical character extraction is implemented on the local motion information to obtain the local motion characteristics of the motion field. Finally, the space distribution relationship of the motion characteristics is expressed by global structured information. A method based on the statistical study is adopted for recognizing behavior styles. The algorithm implements the behavior recognition directly through the analysis based on the motion information to improve the efficiency and the robustness of the algorithm.

In a pattern identification device performing pattern identification of data which has been input by hierarchically extracting features, a primary feature is extracted and distribution of at least one feature extraction result extracted is analyzed, a secondary feature is extracted according to this analysis result. Thus, it is possible to perform pattern identification robustly against fluctuations of the input pattern at a reduced processing cost while reducing the probability of occurrence of incorrect identification.

The invention belongs to the technical field of the pattern identification and image processing, and relates to a license plate detection and identification method based on the maximum stable extremal region, which comprises the following steps: extracting the maximum stable extremal region (MSER) to obtain text regions of candidate license plates; adopting one effective feature for description of each extremal region, classifying the extremal regions into 'text' regions and 'non-text' regions with a classifier obtained in prior training, and extracting a license plate from original images based on the characteristics of the structure of the license plate; and describing with the characteristics of the shape context, and completing the character identification through template matching. Since the maximum stable extremal region has the affine invariance, high stability and multi-scale features, and the regions are determined only according to the gray value and are not light-sensitive,the license plate detection and identification method with the maximum stable extremal region as the base is applicable to the complex background, and has the advantages of good stability and high identification rate.

Systems and methods are provided for extracting features of a building from data having spatial coordinates. The method includes extracting one or more walls and roofs from the data; constructing a building model from the walls and roofs; extracting color data associated with the data and projecting the color data onto the building model; superimposing one or more images onto the building model; applying pattern recognition to extract one or more three-dimensional structural components of the building model; replacing identified three-dimensional structural components with the standard structural elements; comparing subsequent data sets to identify a changed object; and, extracting one or more poles in the building model's vicinity or along the edges of roads.

A plurality of ECG Superscore formulae, created from multiple parameter ECG measurements including those from advanced ECG techniques, can be optimized using additive multivariate statistical models or pattern recognition procedures, with the results compared against a large database of ECG measurements from individuals with known cardiac conditions and / or previous cardiac events. Superscore formulae utilize multiple ECG parameters and accompanying weighting coefficients and allow data obtained from any given patient to be used in calculating that patient's ECG Superscore results. ECG Superscores have retrospectively optimized accuracy for identifying and screening individuals for underlying heart disease and / or for determining the risk of future cardiac events. They thus have greater predictive value than that of any conventional or advanced ECG measurement alone or of any non-optimized combinations of conventional or advanced ECG measurements that have been used in the past. Ongoing optimization of ECG Superscore diagnostic and predictive accuracy may be realized through the iterative adjustment of Superscore formulae based on the incorporation of data from new patients into the database and / or from longitudinal follow-up of the disease and cardiac event status of existing patients.

Generally, the present invention determines and uses spectral peak information, which preferably augments feature vectors and creates augmented feature vectors. The augmented feature vectors decrease errors in pattern recognition, increase noise immunity for wide-band noise, and reduce reliance on noisy formant features. Illustratively, one way of determining spectral peak information is to split pattern data into a number of frequency ranges and determine spectral peak information for each of the frequency ranges. This allows single peak selection. All of the spectral peak information is then used to augment a feature vector. Another way of determining spectral peak information is to use an adaptive Infinite Impulse Response filter to provide this information. Additionally, the present invention can determine and use incremental information. The incremental information is relatively easy to calculate and helps to determine if additional or changed features are worthwhile. The incremental information is preferably determined by determining a difference between mutual information (between the feature vector and the classes to be disambiguated) for new or changed feature vectors and mutual information for old feature vectors.

In many areas, recent developments have generated very large datasets from which it is desired to extract meaningful relationships between the dataset elements. However, to date, the finding of such relationships using prior art methods has proved extremely difficult especially in the biomedical arts. Methods for local causal learning and Markov blanket discovery are important recent developments in pattern recognition and applied statistics, primarily because they offer a principled solution to the variable / feature selection problem and give insight about local causal structure. The present invention provides a generative method for learning local causal structure around target variables of interest in the form of direct causes / effects and Markov blankets applicable to very large datasets and relatively small samples. The method is readily applicable to real-world data, and the selected feature sets can be used for causal discovery and classification. The generative method GLL-PC can be instantiated in many ways, giving rise to novel method variants. In general, the inventive method transforms a dataset with many variables into either a minimal reduced dataset where all variables are needed for optimal prediction of the response variable or a dataset where all variables are direct causes and direct effects of the response variable. The power of the invention and significant advantages over the prior art were empirically demonstrated with datasets from a diversity of application domains (biology, medicine, economics, ecology, digit recognition, text categorization, and computational biology) and data generated by Bayesian networks.

The present invention relates to pattern recognition and classification, more particularly, to a system and method for meta-recognition which can to predict success / failure for a variety of different recognition and classification applications. In the present invention, we define a new approach based on statistical extreme value theory and show its theoretical basis for predicting success / failure based on recognition or similarity scores. By fitting the tails of similarity or distance scores to an extreme value distribution, we are able to build a predictor that significantly outperforms random chance. The proposed system is effective for a variety of different recognition applications, including, but not limited to, face recognition, fingerprint recognition, object categorization and recognition, and content-based image retrieval system. One embodiment includes adapting machine learning approach to address meta-recognition based fusion at multiple levels, and provide an empirical justification for the advantages of these fusion element. This invention provides a new score normalization that is suitable for multi-algorithm fusion for recognition and classification enhancement.

A pattern recognition apparatus compares an image including a photographed object to be recognized with a model previously registered in a table and recognizes the object to be recognized, and the pattern recognition apparatus includes an image input part 1, a feature point extraction part 2, a triangulation part 3, a feature point selection part 4, a basis calculation part 5, a partial pattern structure part 6, an index calculation part 7, a table registration part 8, a pattern similarity calculation part 9, a hypothesis information generation part 10, and an object recognition part 11. Plural feature points are extracted from the image of the object to be recognized, triangulation of a feature point set is obtained, and a combination of plural feature points is selected from plural feature points in accordance with the extracted triangulation.