Abstract:
L'invention concerne un procédé pour la reconnaissance d'objets d'un type prédéfini parmi un ensemble de types,au sein d'un ensemble d'images numériques, comportant - la détection (11) d'un objet de ce type prédéfini au sein d'une image numérique (10) dudit ensemble, et la détermination (12) d'une zone (13) de ladite image englobant l'objet détecté; - la génération (14) d'une signature (15) par un réseau de neurones à convolution à partir de cette zone, permettant une identification de l'objet de façon univoque; - la détermination (16) à partir de la signature d'un ensemble d'attributs (17); - la mémorisation (18) dans une base de données (19) d'un enregistrement relatif audit objet associant la signature à l'ensemble d'attributs; dans lequel le réseau de neurones est entrainé sur un jeu d'apprentissage composées d'un premier ensemble formé d'objets associés à un ensemble d'attributs et d'un second ensemble formé d'objets non associés à un ensemble d'attributs.
Abstract:
A computer-implemented method, computer program product and computing system for receiving non-structured content concerning a plurality of items. The non-structured content is processed to identify one or more proposed features for the plurality of items. The one or more proposed features are provided to a user for review. Feature feedback concerning the one or more proposed features is received. The one or more proposed features are modified based, at least in part, upon the feature feedback received from the user, thus generating one or more approved features
Abstract:
Techniques related to implementing fully convolutional networks for semantic image segmentation are discussed. Such techniques may include combining feature maps from multiple stages of a multi-stage fully convolutional network to generate a hyper-feature corresponding to an input image, up-sampling the hyper-feature and summing it with a feature map of a previous stage to provide a final set of features, and classifying the final set of features to provide semantic image segmentation of the input image.
Abstract:
The disclosed computer-implemented method for efficiently classifying data objects may include (1) receiving a data object to be classified according to a group of rules, where each rule includes one or more clauses, (2) creating, for each rule, a rule evaluation job that directs a rule evaluation processor to evaluate the data object according to the clauses within the rule, where the rule evaluation processor evaluates the clauses in increasing order of estimated processing time, (3) submitting the rule evaluation jobs created for the rules to rule evaluation queues for processing by the rule evaluation processor, where the rule evaluation jobs are submitted in decreasing order of estimated processing time, (4) receiving an evaluation result for each rule evaluation job, and (5) in response to receiving the evaluation results, classifying the data object according to the evaluation results. Various other methods, systems, and computer-readable media are also disclosed.
Abstract:
A processing device executing a scheduler receives, by a device, a schedule from a remote server computing device, the schedule having a compact format that is understood by the device. The device stores the schedule and the processing device parses the schedule to identify a scheduled event. The processing device executes the scheduled event at a specified time in accordance with the schedule even in the absence of a network connection between the device and the remote server computing device.
Abstract:
There is provided a restraint management apparatus. The restraint management apparatus comprises a processing unit arranged to: receive one or more types of sensor data; determine a status of a subject based on the received sensor data; determine, based on the determined subject status, a restraint parameter for a restraint device configured to restrain a body part of the subject; and output a signal based on the determined restraint parameter.
Abstract:
The disclosed techniques can provide users with a tool having an integrated, user- friendly interface and having automated mechanisms which can reveal correlations between data streams to the users in a clear and easily understandable way, thereby enabling the users to easily digest the vast amount of information contained in activities within one or more network, to understand the correlations among the activities, to stay informed and responsive to current or new trends, and even to predict future trends. Among other benefits, the disclosed techniques are especially useful in the context of discovering impacts of social networking activities on other types of commercial activities.
Abstract:
Systems, methods and mediums are described for processing rules and associated bags of facts generated by an application in communication with a processing engine, database and rule engine that process the bags of facts in view of the rules and generate one or more rule-dependent responses to the application which performs one or more work flows based on the responses. The rule engine may apply forward-chaining, backward-chaining or a combination of forward-chaining and backward-chaining to process the rules and facts. Numerous novel applications that work in conjunction with the processing engine, database and rule engine are also described.
Abstract:
A reasoning engine is disclosed. Contemplated reasoning engines acquire data relating to one or more aspects of various environments. Inference engines within the reasoning engines review the acquire data, historical or current, to generate one or more hypotheses about how the aspects of the environments might be correlated, if at all. The reasoning engine can attempt to validate the hypotheses through controlling acquisition of the environment data.
Abstract:
System and processes for optimal selection of teeth for dentures based on the anatomical measurements and bite impressions of the patient. This information is applied in an iterative manner to rules that balance the anatomical and aesthetic considerations to select the best teeth for a patient. The system may also use this information in an iterative manner to rules that balance the anatomical and aesthetic considerations to design the optimal denture base for the patient as well.