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公开(公告)号：US20210248425A1
公开(公告)日：2021-08-12
申请号：US17155452
申请日：2021-01-22
Applicant: NEC Laboratories America, Inc.
Inventor： Bo Zong , Haifeng Chen , Lichen Wang
Abstract: A method for implementing graph-based reinforced text representation learning (GRTR) is presented. The method includes, in a training phase, generating a dependency tree for training text data, training a GRTR agent by learning to navigate in the dependency tree and selectively collecting semantic information, learning GRTR agents, and storing, in a GRTR-specific memory, parameters of the learned GRTR agents. The method further includes, in a testing phase, generating a dependency tree for testing the text data, retrieving and evaluating the learned GRTR agents of the training phase to evaluate testing samples, making task-specific decisions for the testing samples, and reporting the task-specific decisions to a computing device operated by a user.
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公开(公告)号：US11055605B2
公开(公告)日：2021-07-06
申请号：US15785796
申请日：2017-10-17
Applicant: NEC Laboratories America, Inc.
Inventor： Hans Peter Graf , Eric Cosatto , Iain Melvin
IPC: G06N3/08 , G06N3/04 , G01S7/41 , G01S13/931
Abstract: A computer-implemented method executed by a processor for training a neural network to recognize driving scenes from sensor data received from vehicle radar is presented. The computer-implemented method includes extracting substructures from the sensor data received from the vehicle radar to define a graph having a plurality of nodes and a plurality of edges, constructing a neural network for each extracted substructure, combining the outputs of each of the constructed neural networks for each of the plurality of edges into a single vector describing a driving scene of a vehicle, and classifying the single vector into a set of one or more dangerous situations involving the vehicle.
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公开(公告)号：US20210192377A1
公开(公告)日：2021-06-24
申请号：US17116479
申请日：2020-12-09
Applicant: NEC Laboratories America, Inc.
Inventor： Christopher Malon , Nitish Joshi
Abstract: A method trains an inference model on two-hop NLI problems that include a first and second premise and a hypothesis, and further includes generating, by the model using hypothesis reduction, an explanation from an input premise and an input hypothesis, for an input single hop NLI problem. The learning step determines a distribution over extraction starting positions and lengths from within the first premise and hypothesis of a two-hop NLI problem. The learning step k extraction output slots with combinations of words from the first premise of the two-hop NLI problem and fills another extraction output slots with combinations of words from the hypothesis of the two-hop NLI problem. The learning step trains a sequence model by using the extraction output slots and the other extraction output slots together with the second premise as an input to a single-hop NLI classifier to output a label of the two-hop NLI problem.
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公开(公告)号：US11043786B2
公开(公告)日：2021-06-22
申请号：US15956284
申请日：2018-04-18
Applicant: NEC Laboratories America, Inc.
Inventor： Fatih Yaman , Shaoliang Zhang , Eduardo Mateo Rodriguez , Kohei Nakamura , Yoshihisa Inada , Takanori Inoue
IPC: H01S3/067 , G02B6/44 , G02B6/02 , H01S3/23 , H01S3/094 , H01S3/16 , H01S3/0941 , H01S5/10 , H01S5/20 , H01S5/40
Abstract: Aspects of the present disclosure describe systems, methods, and structures that advantageously amplify optical signals through the effect of optical pump signals generated by a multicore laser diode and multicore rare-earth doped optical fiber in optical communication with a 3D waveguide structure and a multicore input signal fiber providing a plurality of optical signals for amplification.
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公开(公告)号：US20210158490A1
公开(公告)日：2021-05-27
申请号：US17090508
申请日：2020-11-05
Applicant: NEC Laboratories America, Inc.
Inventor： Quoc-Huy Tran , Bingbing Zhuang , Pan Ji , Manmohan Chandraker
Abstract: A method for jointly removing rolling shutter (RS) distortions and blur artifacts in a single input RS and blurred image is presented. The method includes generating a plurality of RS blurred images from a camera, synthesizing RS blurred images from a set of GS sharp images, corresponding GS sharp depth maps, and synthesized RS camera motions by employing a structure-and-motion-aware RS distortion and blur rendering module to generate training data to train a single-view joint RS correction and deblurring convolutional neural network (CNN), and predicting an RS rectified and deblurred image from the single input RS and blurred image by employing the single-view joint RS correction and deblurring CNN.
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Patent Agency Ranking
公开(公告)号：US20210150751A1
公开(公告)日：2021-05-20
申请号：US17095967
申请日：2020-11-12
Applicant: NEC Laboratories America, Inc.
Inventor： Buyu Liu , Samuel Schulter , Manmohan Chandraker
Abstract: Methods and systems for occlusion detection include detecting a set of foreground object masks in an image, including a mask of a visible portion of a foreground object and a mask of the foreground object that includes at least one occluded portion, using a machine learning model. A set of background object masks is detected in the image, including a mask of a visible portion of a background object and a mask of the background object that includes at least one occluded portion, using the machine learning model. The set of foreground object masks and the set of background object masks are merged using semantic merging. A computer vision task is performed that accounts for the at least one occluded portion of at least one object of the merged set.
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公开(公告)号：US20210150275A1
公开(公告)日：2021-05-20
申请号：US17094261
申请日：2020-11-10
Applicant: NEC Laboratories America, Inc.
Inventor： Samuel Schulter , Gaurav Sharma , Yi-Hsuan Tsai , Manmohan Chandraker , Xiangyun Zhao
Abstract: Methods and systems for object detection include training dataset-specific object detectors using respective annotated datasets, each of the annotated datasets including annotations for a respective set of one or more object classes. The annotated datasets are cross-annotated using the dataset-specific object detectors. A unified object detector is trained, using the cross-annotated datasets, to detect all of the object classes of the annotated datasets. Objects are detected in an input image using the unified object detector.
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158.发明申请公开(公告)号：US20210150240A1
公开(公告)日：2021-05-20
申请号：US17091140
申请日：2020-11-06
Applicant: NEC Laboratories America, Inc.
Inventor： Xiang Yu , Buyu Liu , Manmohan Chandraker , Junru Wu
Abstract: A computer-implemented method for implementing face spoofing detection using a physical-cue-guided multi-source multi-channel framework includes receiving a set of data including face recognition data, liveness data and material data associated with at least one face image, obtaining a shared feature from the set of data using a backbone neural network structure, performing, based on the shared feature, a pretext task corresponding to face recognition, a first proxy task corresponding to depth estimation, a liveness detection task, and a second proxy task corresponding to material prediction, and aggregating outputs of the pretext task, the first proxy task, the liveness detection task and the second proxy task using an attention mechanism to boost face spoofing detection performance.
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公开(公告)号：US20210148727A1
公开(公告)日：2021-05-20
申请号：US17090399
申请日：2020-11-05
Applicant: NEC Laboratories America, Inc.
Inventor： Sriram Nochur Narayanan , Manmohan Chandraker
Abstract: A method for simultaneous multi-agent recurrent trajectory prediction is presented. The method includes reconstructing a topological layout of a scene from a dataset including real-world data, generating a road graph of the scene, the road graph capturing a hierarchical structure of interconnected lanes, incorporating vehicles from the scene on the generated road graph by utilizing tracklet information available in the dataset, assigning the vehicles to their closest lane identifications, and identifying diverse plausible behaviors for every vehicle in the scene. The method further includes sampling one behavior from the diverse plausible behaviors to select an associated velocity profile sampled from the real-world data of the dataset that resembles the sampled one behavior and feeding the road graph and the sampled velocity profile with a desired destination to a dynamics simulator to generate a plurality of simulated diverse trajectories output on a visualization device.
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公开(公告)号：US10999247B2
公开(公告)日：2021-05-04
申请号：US16169012
申请日：2018-10-24
Applicant: NEC Laboratories America, Inc.
Inventor： Bo Zong , Daeki Cho , Cristian Lumezanu , Haifeng Chen , Qi Song
Abstract: Systems and methods for preventing cyberattacks using a Density Estimation Network (DEN) for unsupervised anomaly detection, including constructing the DEN using acquired network traffic data by performing end-to-end training. The training includes generating low-dimensional vector representations of the network traffic data by performing dimensionality reduction of the network traffic data, predicting mixture membership distribution parameters for each of the low-dimensional representations by performing density estimation using a Gaussian Mixture Model (GMM) framework, and formulating an objective function to estimate an energy and determine a density level of the low-dimensional representations for anomaly detection, with an anomaly being identified when the energy exceeds a pre-defined threshold. Cyberattacks are prevented by blocking transmission of network flows with identified anomalies by directly filtering out the flows using a network traffic monitor.
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