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    Recommender system for heterogeneous log pattern editing operation
    611.
    发明授权
    Recommender system for heterogeneous log pattern editing operation 有权

    公开(公告)号：US10929763B2

    公开(公告)日：2021-02-23

    申请号：US15684293

    申请日：2017-08-23

    Applicant: NEC Laboratories America, Inc.

    Inventor： Jianwu Xu ,  Biplob Debnath ,  Bo Zong ,  Hui Zhang ,  Guofei Jiang ,  Hancheng Ge

    IPC: G06N5/04 ,  G06F17/16 ,  G06N7/00 ,  G06F40/00 ,  G06F40/16 ,  G06F40/284

    Abstract: A heterogeneous log pattern editing recommendation system and computer-implemented method are provided. The system has a processor configured to identify, from heterogeneous logs, patterns including variable fields and constant fields. The processor is also configured to extract a category feature, a cardinality feature, and a before-after n-gram feature by tokenizing the variable fields in the identified patterns. The processor is additionally configured to generate target similarity scores between target fields to be potentially edited and other fields from among the variable fields in the heterogeneous logs using pattern editing operations based on the extracted category feature, the extracted cardinality feature, and the extracted before-after n-gram feature. The processor is further configured to recommend, to a user, log pattern edits for at least one of the target fields based on the target similarity scores between the target fields in the heterogeneous logs.

    SELF-SUPERVISED VISUAL ODOMETRY FRAMEWORK USING LONG-TERM MODELING AND INCREMENTAL LEARNING
    612.
    发明申请
    SELF-SUPERVISED VISUAL ODOMETRY FRAMEWORK USING LONG-TERM MODELING AND INCREMENTAL LEARNING 有权

    公开(公告)号：US20210042937A1

    公开(公告)日：2021-02-11

    申请号：US16939604

    申请日：2020-07-27

    Applicant: NEC Laboratories America, Inc.

    Inventor： Pan Ji ,  Quoc-Huy Tran ,  Manmohan Chandraker ,  Yuliang Zou

    IPC: G06T7/246 ,  G06T7/579

    Abstract: A computer-implemented method for implementing a self-supervised visual odometry framework using long-term modeling includes, within a pose network of the self-supervised visual odometry framework including a plurality of pose encoders, a convolution long short-term memory (ConvLSTM) module having a first-layer ConvLSTM and a second-layer ConvLSTM, and a pose prediction layer, performing a first stage of training over a first image sequence using photometric loss, depth smoothness loss and pose cycle consistency loss, and performing a second stage of training to finetune the second-layer ConvLSTM over a second image sequence longer than the first image sequence.

    System and method for detecting security risks in a computer system
    615.
    发明授权
    System and method for detecting security risks in a computer system 有权

    公开(公告)号：US10909242B2

    公开(公告)日：2021-02-02

    申请号：US16169081

    申请日：2018-10-24

    Applicant: NEC Laboratories America, Inc.

    Inventor： Ding Li ,  Xusheng Xiao ,  Zhichun Li ,  Guofei Jiang ,  Peng Gao

    IPC: G06F21/55 ,  G06F9/54 ,  G06F16/33 ,  G06F21/57 ,  G06F16/2455

    Abstract: A system and method are provided for identifying security risks in a computer system. The system includes an event stream generator configured to collect system event data from the computer system. The system further includes a query device configured to receive query requests that specify parameters of a query. Each query request includes at least one anomaly model. The query request and the anomaly model are included in a first syntax in which a system event is expressed as {subject-operation-object}. The system further includes a detection device configured to receive at least one query request from the query device and continuously compare the system event data to the anomaly models of the query requests to detect a system event that poses a security risk. The system also includes a reporting device configured to generate an alert for system events that pose a security risk detected by the detection device.

    WORD-OVERLAP-BASED CLUSTERING CROSS-MODAL RETRIEVAL
    616.
    发明申请
    WORD-OVERLAP-BASED CLUSTERING CROSS-MODAL RETRIEVAL 有权

    公开(公告)号：US20210027019A1

    公开(公告)日：2021-01-28

    申请号：US16918353

    申请日：2020-07-01

    Applicant: NEC Laboratories America, Inc. ,  NEC Corporation

    Inventor： Yuncong Chen ,  Hao Yuan ,  Dongjin Song ,  Cristian Lumezanu ,  Haifeng Chen ,  Takehiko Mizoguchi

    IPC: G06F40/30 ,  G06N3/08 ,  G06K9/62 ,  G06F17/16

    Abstract: A system for cross-modal data retrieval is provided that includes a neural network having a time series encoder and text encoder which are jointly trained using an unsupervised training method which is based on a loss function. The loss function jointly evaluates a similarity of feature vectors of training sets of two different modalities of time series and free-form text comments and a compatibility of the time series and the free-form text comments with a word-overlap-based spectral clustering method configured to compute pseudo labels for the unsupervised training method. The computer processing system further includes a database for storing the training sets with feature vectors extracted from encodings of the training sets. The encodings are obtained by encoding a training set of the time series using the time series encoder and encoding a training set of the free-form text comments using the text encoder.

    Learning good features for visual odometry
    619.
    发明授权
    Learning good features for visual odometry 有权

    公开(公告)号：US10852749B2

    公开(公告)日：2020-12-01

    申请号：US16100445

    申请日：2018-08-10

    Applicant: NEC Laboratories America, Inc.

    Inventor： Quoc-Huy Tran ,  Manmohan Chandraker ,  Hyo Jin Kim

    IPC: G05D1/08 ,  G06T7/73 ,  G05D1/00 ,  G08G5/04 ,  B64C39/02 ,  G08G5/00 ,  G06N3/04 ,  G06N3/08 ,  G06N5/04 ,  G06T7/00 ,  G06F16/29 ,  G01C21/32

    Abstract: A computer-implemented method, system, and computer program product are provided for pose estimation. The method includes receiving, by a processor, a plurality of images from one or more cameras. The method also includes generating, by the processor with a feature extraction convolutional neural network (CNN), a feature map for each of the plurality of images. The method additionally includes estimating, by the processor with a feature weighting network, a score map from a pair of the feature maps. The method further includes predicting, by the processor with a pose estimation CNN, a pose from the score map and a combined feature map. The method also includes controlling an operation of a processor-based machine to change a state of the processor-based machine, responsive to the pose.

    AERIAL FIBER OPTIC CABLE LOCALIZATION BY DISTRIBUTED ACOUSTIC SENSING
    620.
    发明申请
    AERIAL FIBER OPTIC CABLE LOCALIZATION BY DISTRIBUTED ACOUSTIC SENSING 审中-公开

    公开(公告)号：US20200319017A1

    公开(公告)日：2020-10-08

    申请号：US16838105

    申请日：2020-04-02

    Applicant: NEC Laboratories America, Inc.

    Inventor： Yue TIAN

    IPC: G01H9/00 ,  G02B6/44

    Abstract: Aspects of the present disclosure describe aerial fiber optical cable localization using distributed acoustic sensing (DAS) that advantageously may determine the locality of electrical transformers affixed to utility poles along with the aerial fiber optical cable as well as any length(s) of fiber optical cable between the poles. Further aspects employ survey manned or unmanned, aerial or terrestrial survey vehicles that acoustically excite locations along the fiber optical cable and associate those DAS excitations with global positioning location (GPS).

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