SYSTEM AND METHOD FOR PRECISE IMAGE INPAINTING TO REMOVE UNWANTED CONTENT FROM DIGITAL IMAGES

    公开(公告)号:US20210158491A1

    公开(公告)日:2021-05-27

    申请号:US16950835

    申请日:2020-11-17

    Abstract: An inpainting method includes retrieving image information at an electronic device, where the image information identifies an area within an image. The method also includes retrieving, using the electronic device, semantic information including a plurality of semantic classes and a semantic class distribution for each semantic class of the plurality of semantic classes. The method further includes generating semantic codes associated with different portions of the image based on the image information and the semantic information. In addition, the method includes constructing the area within the image by generating image content based on the semantic information.

    Predicting user actions on ubiquitous devices

    公开(公告)号:US10885905B2

    公开(公告)日:2021-01-05

    申请号:US16235983

    申请日:2018-12-28

    Abstract: A method includes that for each model from multiple models, evaluating a model prediction accuracy based on a dataset of a user over a first time duration. The dataset includes a sequence of actions with corresponding contexts based on electronic device interactions. Each model is trained to predict a next action at a time point within the first time duration, based on a first behavior sequence over a first time period from the dataset before the time point, a second behavior sequence over a second time period from the dataset before the time point, and context at the time point. A model is selected from the multiple models based on its model prediction accuracy for the user based on a domain. An action to be initiated at a later time using an electronic device of the user is recommended using the selected model during a second time duration.

    MULTI-MODEL STRUCTURES FOR CLASSIFICATION AND INTENT DETERMINATION

    公开(公告)号:US20200334539A1

    公开(公告)日:2020-10-22

    申请号:US16728987

    申请日:2019-12-27

    Abstract: Intent determination based on one or more multi-model structures can include generating an output from each of a plurality of domain-specific models in response to a received input. The domain-specific models can comprise simultaneously trained machine learning models that are trained using a corresponding local loss metric for each domain-specific model and a global loss metric for the plurality of domain-specific models. The presence or absence of an intent corresponding to one or more domain-specific models can be determined by classifying the output of each domain-specific model.

    SYSTEM AND METHOD FOR GENERATING ASPECT-ENHANCED EXPLAINABLE DESCRIPTION-BASED RECOMMENDATIONS

    公开(公告)号:US20190392330A1

    公开(公告)日:2019-12-26

    申请号:US16246775

    申请日:2019-01-14

    Abstract: A recommendation method includes determining one or more aspects of a first item based on at least one descriptive text of the first item. The recommendation method also includes updating a knowledge graph containing nodes that represent multiple items, multiple users, and multiple aspects. Updating the knowledge graph includes linking one or more nodes representing the one or more aspects of the first item to a node representing the first item with one or more first edges. Each of the one or more first edges identifies weights associated with (i) user sentiment about the associated aspect of the first item and (ii) an importance of the associated aspect to the first item. In addition, the recommendation method includes recommending a second item for a user with an explanation based on at least one aspect linked to the second item in the knowledge graph.

    MALWARE DETECTION BY EXPLOITING MALWARE RE-COMPOSITION VARIATIONS USING FEATURE EVOLUTIONS AND CONFUSIONS

    公开(公告)号:US20170353481A1

    公开(公告)日:2017-12-07

    申请号:US15388460

    申请日:2016-12-22

    Abstract: One embodiment provides a method comprising, in a training phase, receiving one or more malware samples, extracting multi-aspect features of malicious behaviors triggered by the malware samples, determining evolution patterns of the malware samples based on the multi-aspect features, and predicting mutations of the malware samples based on the evolution patterns. Another embodiment provides a method comprising, in a testing phase, receiving a new mobile application, extracting a first set of multi-aspect features for the new mobile application using a learned feature model, and determining whether the new mobile application is a mutation of a malicious application using a learned classification model and the first set of multi-aspect features.

    Acoustic-based communication between devices

    公开(公告)号:US09686397B1

    公开(公告)日:2017-06-20

    申请号:US15280325

    申请日:2016-09-29

    CPC classification number: H04B11/00 Y02D70/142 Y02D70/144 Y02D70/26 Y02D70/48

    Abstract: A modulation method referred to as Time Shift Keying (TSK) is used to transmit messages between two devices in a highly energy efficient manner. A message represented by an inaudible audio signal is modulated on a transmitting device. The audio signal is comprised of an array of non-zero amplitude delimiter signals with time periods of zero-amplitude transmission between delimiters. The time duration of the zero-amplitude transmission periods is mapped to a symbol, multiple symbols are then assembled into a message. On the transmitting device, the audio signal is broken into pieces or sequences of bits which are mapped to symbols. On the receiving device, the time durations of zero-amplitude transmission are translated to the symbols which are assembled to the message. The delimiter signals have gradually increasing and decreasing amplitudes and have a length such that make them detectable by the receiving device.

    SYSTEM AND METHOD FOR PRIVACY MANAGEMENT OF INFINITE DATA STREAMS

    公开(公告)号:US20170109544A1

    公开(公告)日:2017-04-20

    申请号:US15294570

    申请日:2016-10-14

    CPC classification number: G06F21/6254 G06F21/6245 H04L63/0407 H04L63/0421

    Abstract: An apparatus, method, and computer readable medium for management of infinite data streams. The apparatus includes a memory that stores streaming data with a data set and a processor operably connected to the memory. The processor transforms the data set to a second data set. To transform the data set, the processor determines whether a difference level exceeds a threshold, and transforms the data set by adding a noise when the difference level exceeds the threshold. When the difference level does not exceed the threshold, the processor determines whether a retroactive count is greater than a threshold, transforms the data set by adding a second noise when the retroactive count is greater than the threshold, and transforms the data set by adding a third noise when the retroactive count is not greater than the threshold. The processor transmits the second data set to a data processing system for further processing.

    Computing system with privacy mechanism and method of operation thereof
    130.
    发明授权
    Computing system with privacy mechanism and method of operation thereof 有权
    具有隐私机制的计算系统及其操作方法

    公开(公告)号:US09053345B2

    公开(公告)日:2015-06-09

    申请号:US13896030

    申请日:2013-05-16

    Abstract: A computing system includes: an initialization module configured to generate initial sharing options; a rating analysis module, coupled to the initialization module, configured to generate a privacy score and a benefit score with a control unit for one or more of the initial sharing options; a mapping module, coupled to the rating analysis module, configured to generate a map based on the initial sharing options, the privacy score, and the benefit score; and a tuning module, coupled to the mapping module, configured to: analyze an initial distribution of the map, and generate the tuned sharing options based on the initial distribution for displaying on a device.

    Abstract translation: 计算系统包括:初始化模块,被配置为产生初始共享选项; 耦合到所述初始化模块的评估分析模块被配置为利用用于一个或多个初始共享选项的控制单元生成隐私分数和利益分数; 耦合到所述评估分析模块的映射模块,被配置为基于所述初始共享选项,所述隐私分数和所述收益分数生成地图; 以及耦合到所述映射模块的调谐模块,被配置为:分析所述映射的初始分布,并且基于用于在设备上显示的初始分布来生成所述调谐共享选项。

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