6067 results about "Feature based" patented technology

The invention provides a method, system, and computer usable medium including a program for sponsoring customizing feed content. The method includes associating a user with a profile group based on characteristic response data; receiving at least one keyword from the user; determining whether feed formatted content contains the keyword; associating a sponsorship with the feed formatted content based on the keyword and the associated profile group; and providing the feed formatted content with associated sponsorship to the user based on the determination.

This provides for controlling mobile device functions and features. For example, it limits or disables the use of some of mobile device features which could cause distraction to the user, when the user is engaged in another activity. In an example, it enables other mobile device features based on occurrence of events related to the user or environment. Another example addresses controlling the mobile device features, such as SMS, while the user is in a vehicle or driving. Another example restricts the ability of the driver of a vehicle to text, while the vehicle is in motion, by automatically disabling the texting ability of mobile device within and around the perimeter of the driver's seat. Other variations, examples, improvements, detection mechanisms, models, techniques, calculations, verification mechanisms, and features are also described in details.

This provides for controlling mobile device functions and features, along with systems incorporating these devices and methods. For example, it limits or disables the use of some of mobile device features which could cause distraction to the user, when the user is engaged in another activity. In an example, it enables other mobile device features based on occurrence of events related to the user or environment. Another example addresses controlling the mobile device features, such as SMS, while the user is in a vehicle or driving. Another example restricts the ability of the driver of a vehicle to text, while the vehicle is in motion, by automatically disabling the texting ability of mobile device within and around the perimeter of the driver's seat. Other variations, examples, improvements, detection mechanisms, models, techniques, calculations, verification mechanisms, and features are also described in details.

The present invention provides methods and systems for patient-specific seizure onset detection. In one embodiment, at least one EEG waveform of the patient is recorded, and at least one epoch (sample) of the waveform is extracted. The waveform sample is decomposed into one or more subband signals via a wavelet decomposition of the waveform sample, and one or more feature vectors are computed based on the subband signals. A seizure onset can then be identified based on classification of the feature vectors to a seizure or a non-seizure class by comparing the feature vectors with a decision measure previously computed for that patient. The decision measure can be derived based on reference seizure and non-seizure EEG waveforms of the patient. In another aspect, similar methodology is employed for automatic detection of alpha waves. In other aspects, the invention provides diagnostic and imaging systems that incorporate the above seizure-onset and alpha-wave detection methodology.

A system for preventing driving skill atrophy comprises a trainer module that determines the driver's current skill level, disables certain automated features based on the determined skill level, and forces the driver to use and hone her driving skills. The system collects data to determine through on-board vehicle sensors how a driver is driving the vehicle. The system then compares the driver's current driving skills with the driver's historical driving skills or the general population's driving skills. Based on the comparison, the system determines whether the driver's skill level is stagnant, improving or deteriorating. If the skill level is improving, for example, the system disables certain automated driving features to give driver more control of the vehicle.

A computerized mortgage loan system and process to enable borrowers to design mortgage loans that meet their particular individual needs and financial goals, and that can be adapted to fit changing needs and goals is provided. The loan requirements of the borrower are obtained and applied to a set of rules for combining loan product features. One or more loan recommendations are determined and presented to the borrower. The loan recommendations include customized combinations of loan features based on the loan requirements of the borrower and the rules.

Portions from segment boundary regions of a plurality of speech segments are extracted. Each segment boundary region is based on a corresponding initial unit boundary. Feature vectors that represent the portions in a vector space are created. For each of a plurality of potential unit boundaries within each segment boundary region, an average discontinuity based on distances between the feature vectors is determined. For each segment, the potential unit boundary associated with a minimum average discontinuity is selected as a new unit boundary.

One embodiment of the present invention provides a system that determines a location in a layout to place an assist feature. During operation, the system receives a layout of an integrated circuit. Next, the system selects an evaluation point in the layout. The system then chooses a candidate location in the layout for placing an assist feature. Next, the system determines the final location in the layout to place an assist feature by, iteratively, (a) selecting perturbation locations for placing representative assist features in the proximity of the candidate location, (b) computing aerial-images using an image intensity model, the layout, and by placing representative assist features at the candidate location and the perturbation locations, (c) calculating image-gradient magnitudes at the evaluation point based on the aerial-images, and (d) updating the candidate location for the assist feature based on the image-gradient magnitudes.

The system of the present invention allows a user to generate a representation of time-based media. The system of the present invention includes a feature extraction module for extracting features from media content. For example, the feature extraction module can detect solos in a musical performance, or can detect music, applause speech, and the like. A formatting module formats a media representation generated by the system. The formatting module also applies feature extraction information to the representation, and formats the representation according to a representation specification. In addition, the system can include an augmented output device that generates a media representation based on the feature extraction information and the representation specification. The methods of the present invention include extracting features from media content, and formatting a media representation being generated using the extracted features and based on a specification or data structure specifying the representation format. The methods can also include generating a media representation based on the results of the formatting.

Fingerprint image processing methods for fingerprint security systems, for example, in wireless communications devices, including capturing fingerprint images (320), identifying features from images (330), matching the identified features with reference features (340), and providing access to the device based upon feature matching (350) results. In one embodiment, minutiae features are extracted from the image and matched to reference minutiae features.

The invention discloses a small target detection method based on feature fusion and depth learning, which solves the problems of poor detection accuracy and real-time performance for small targets. The implementation scheme is as follows: extracting high-resolution feature map through deeper and better network model of ResNet 101; extracting Five successively reduced low resolution feature maps from the auxiliary convolution layer to expand the scale of feature maps. Obtaining The multi-scale feature map by the feature pyramid network. In the structure of feature pyramid network, adopting deconvolution to fuse the feature map information of high-level semantic layer and the feature map information of shallow layer; performing Target prediction using feature maps with different scales and fusion characteristics; adopting A non-maximum value to suppress the scores of multiple predicted borders and categories, so as to obtain the border position and category information of the final target. The invention has the advantages of ensuring high precision of small target detection under the requirement of ensuring real-time detection, can quickly and accurately detect small targets in images, and can be used for real-time detection of targets in aerial photographs of unmanned aerial vehicles.

Corresponding to a target torque, the control device calculates a target value of a feature based on at least one of the length of a long axis of a current vector locus and the length of the short axis and further superimposes a superimposed current on a drive current for the motor, the superimposed current having a frequency different from the frequency of the drive current. Further, the control device detects an actual value of the feature based on at least one of the length of a long axis of a current vector locus of the superimposed current and the length of the short axis of the same and finally detects a phase angle of the motor based on the target value and the actual value for the feature. The manipulation of a detecting phase is performed by feedback of a feature obtained by the magnitude of the superimposed current. That is, when the actual feature is more than the target value, the detecting phase is advanced. Conversely, when the actual feature is less than the target value, the detecting phase is delayed.

An image partitioner is configured to find a partition point that divides a received image into four sub-images each having a pre-selected activated pixel count. A recursion processor is configured to (i) apply the image partitioner to an input image to generate a first partition point and four sub-images and to (ii) recursively apply the image partitioner to at least one of the four sub-images for at least one recursion iteration to generate at least one additional partition point. A formatter is configured to generate a features representation of the input image in a selected format. The features representation is based at least in part on the partition points. The features representation can be used in various ways, such as by a classifier configured to classify the input image based on the features representation.

A method for using a virtual card is provided. In one example, the method includes identifying a geographic identifier for a mobile computing device and matching the geographic identifier with at least one virtual card associated with the mobile computing device. The method further includes triggering at least one virtual card feature based on a matched geographic identifier. In some examples, the at least one virtual card feature includes presenting the at least one virtual card with the matched geographic identifier. In other examples, the at least one virtual card feature includes a security feature including selectively enabling a virtual card transaction based on the at least one virtual card with the matched geographic identifier.

An apparatus, method, and computer program product are provided for generating an image representation. The method includes receiving an input digital image, extracting features from the image which are representative of patches of the image, generating weighting factors for the features based on location relevance data for the image, and weighting the extracted features with the weighting factors to form a representation of the image.

Disclosed are methods for detecting and / or prioritizing phenotype-causing genomic variants and related software tools. The methods include genomic feature based analysis and can combine variant frequency information with sequence characteristics such as amino acid substation. The methods disclosed are useful in any genomics study; for example, rare and common disease gene discovery, tumor growth mutation detection, personalized medicine, agricultural analysis, and centennial analysis.

The present invention relates to systems and methods that determine intent for received data (e.g., email, voice, graphics . . . ) and respond to the data based on the intent. The systems and methods employ various combinations of features based on shallow and deep linguistic analysis (e.g., semantic and syntactic) to yield very high accuracy. The systems and methods analyze and categorize received data to locate data that can include intent. This data can be further refined by extracting features related to the intent. The features can be utilized by a classifier to determine the intent. If the intent warrants a response, the data are further scrutinized and reformulated to generate a description that is indicative of the intent. The reformulation can include representing the features in a logical form, transforming the form and generating a description of the intent that can be presented to a user visually and / or audibly.

A feature-based rapid modeling system that enables a user to construct structural feature models from feature objects representing structural features. The interface enables the rapid construction by allowing for the use of group- and pattern-based feature objects, and by allowing a user to select feature objects based on object properties and object relationship properties, including hierarchical properties. A modeling engine constructs member models based on the feature models, which can be exported to a structure library. The models in the structure library can be imported into new projects, eliminating the need to repeat the construction of the model.

An image retrieval system performs both keyword-based and content-based image retrieval. A user interface allows a user to specify queries using a combination of keywords and examples images. Depending on the input query, the image retrieval system finds images with keywords that match the keywords in the query and / or images with similar low-level features, such as color, texture, and shape. The system ranks the images and returns them to the user. The user interface allows the user to identify images that are more relevant to the query, as well as images that are less or not relevant to the query. The user may alternatively elect to refine the search by selecting one example image from the result set and submitting its low-level features in a new query. The image retrieval system monitors the user feedback and uses it to refine any search efforts and to train itself for future search queries. In the described implementation, the image retrieval system seamlessly integrates feature-based relevance feedback and semantic-based relevance feedback.

The present invention relates to systems and methods that determine intent for received data (e.g., email, voice, graphics . . . ) and respond to the data based on the intent. The systems and methods employ various combinations of features based on shallow and deep linguistic analysis (e.g., semantic and syntactic) to yield very high accuracy. The systems and methods analyze and categorize received data to locate data that can include intent. This data can be further refined by extracting features related to the intent. The features can be utilized by a classifier to determine the intent. If the intent warrants a response, the data are further scrutinized and reformulated to generate a description that is indicative of the intent. The reformulation can include representing the features in a logical form, transforming the form and generating a description of the intent that can be presented to a user visually and / or audibly.

A system and method for predicting victims and detecting fake accounts in OSNs, comprising: a feature-based classifier for predicting victims by classifying, with a classification probability, a target variable of each user in the OSN social graph; a graph-transformer for transforming the social graph into a defense graph by reassigning edge weights to incorporate victim predictions using the classification probability, a graph-based detector for detecting fake users by computing through the power iteration method a probability of a random walk to land on each node in the defense graph after 0(log n) steps, assigning to each node a rank value equal to a node's landing probability normalized by the node degree, sorting the nodes by their rank value and estimating a detection threshold such that each node whose rank value is smaller than the detection threshold is flagged as representing a fake account.

The property of cardiac tissue at a local site, a plurality of sites of in a region of a heart may be characterized based on local electrograms measured at the local site, at a plurality of sites or in the region, respectively. The property may be characterized by normalizing the local electrogram, extracting a feature vector from the normalized electrogram, and classifying the tissue property based on the feature vector. The method of may further include computing a map of the tissue property and treating the tissue based on the resultant map. Apparatus to characterize the property includes a catheter and a processor to normalize the local electrogram, extract the feature vector from the electrogram and classify the tissue based on the feature vector.

The shapes of many natural or man-made objects have curve features. The images of such curves usually do not have sufficient distinctive features to apply conventional feature-based reconstruction algorithms. In this paper, we introduce a photogrammetric method for recovering free-form objects with curvilinear structures. Our method chooses to define the topology and recover a sparse 3D wireframe of the object first instead of directly recovering a surface or volume model. Surface patches covering the object are then constructed to interpolate the curves in this wireframe while satisfying certain heuristics such as minimal bending energy. The result is an object surface model with curvilinear structures from a sparse set of images. We can produce realistic texture-mapped renderings of the object model from arbitrary viewpoints. Reconstruction results on multiple real objects are presented to demonstrate the effectiveness of our approach.

A system and method for determining image similarity. The method includes the steps of automatically providing perceptually significant features of main subject or background of a first image; automatically providing perceptually significant features of main subject or background of a second image; automatically comparing the perceptually significant features of the main subject or the background of the first image to the main subject or the background of the second image; and providing an output in response thereto. In the illustrative implementation, the features are provided by a number of belief levels, where the number of belief levels are preferably greater than two. The perceptually significant features include color, texture and / or shape. In the preferred embodiment, the main subject is indicated by a continuously valued belief map. The belief values of the main subject are determined by segmenting the image into regions of homogenous color and texture, computing at least one structure feature and at least one semantic feature for each region, and computing a belief value for all the pixels in the region using a Bayes net to combine the features. In an illustrative application, the inventive method is implemented in an image retrieval system. In this implementation, the inventive method automatically stores perceptually significant features of the main subject or background of a plurality of first images in a database to facilitate retrieval of a target image in response to an input or query image. Features corresponding to each of the plurality of stored images are automatically sequentially compared to similar features of the query image. Consequently, the present invention provides an automatic system and method for controlling the feature extraction, representation, and feature-based similarity retrieval strategies of a content-based image archival and retrieval system based on an analysis of main subject and background derived from a continuously valued main subject belief map.

An image processing apparatus includes an extracting unit configured to extract a feature point from a captured image; a recognizing unit configured to recognize a position of the feature point; a display control unit configured to perform control, based on the position of the feature point, to display a feature-point pointer indicating the feature point; and an issuing unit configured to issue, based on the position of the feature point, a command corresponding to the position of the feature point or a motion of the feature point.

The present invention provides systems and methods that rank search results. Such ranking typically includes determining a relevance of individual search results via one or more feature-based relevance functions. These functions can be tailored to users and / or applications, and typically are based on scoped information (e.g., lexical), digital artifact author related attributes, digital artifact source repository attributes, and / or relationships between features, for example. In addition, relevance functions can be generated via training sets (e.g., machine learning) or initial guesses that are iteratively refined over time. Upon determining relevance, search results can be ordered with respect to one another, based on respective relevances. Additionally, thresholding can be utilized to mitigate returning results likely to be non-relevant to the query, user and / or application.