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公开(公告)号：US10402658B2
公开(公告)日：2019-09-03
申请号：US15794802
申请日：2017-10-26
Applicant: NEC Laboratories America, Inc.
Inventor： Renqiang Min , Yunchen Pu
IPC: G06K9/00 , G06K9/46 , G06N3/04 , G06K9/66 , H04N5/278 , G06K9/62 , H04N21/218 , H04N21/234 , H04N21/488 , G06K9/72 , H04N7/18
Abstract: A video retrieval system is provided, that includes a set of servers, configured to retrieve a video sequence from a database and forward it to a requesting device responsive to a match between an input text and a caption for the video sequence. The servers are further configured to translate the video sequence into the caption by (A) applying a C3D to image frames of the video sequence to obtain therefor (i) intermediate feature representations across L convolutional layers and (ii) top-layer features, (B) producing a first word of the caption for the video sequence by applying the top-layer features to a LSTM, and (C) producing subsequent words of the caption by (i) dynamically performing spatiotemporal attention and layer attention using the representations to form a context vector, and (ii) applying the LSTM to the context vector, a previous word of the caption, and a hidden state of the LSTM.
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公开(公告)号：US20190244513A1
公开(公告)日：2019-08-08
申请号：US16248897
申请日：2019-01-16
Applicant: NEC Laboratories America, Inc.
Inventor： Alexandru Niculescu-Mizil , Renqiang Min , Eric Cosatto , Farley Lai , Hans Peter Graf , Xavier Fontaine
CPC classification number: G08B29/186 , G06K9/4604 , G06K9/6256 , G06T3/403 , G06T7/0004 , G06T7/001 , G06T2207/20081 , G06T2207/20084
Abstract: A false alarm reduction system and method are provided for reducing false alarms in an automatic defect detection system. The false alarm reduction system includes a defect detection system, generating a list of image boxes marking detected potential defects in an input image. The false alarm reduction system further includes a feature extractor, transforming each of the image boxes in the list into a respective set of numerical features. The false alarm reduction system also includes a classifier, computing as a classification outcome for the each of the image boxes whether the detected potential defect is a true defect or a false alarm responsive to the respective set of numerical features for each of the image boxes.
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223.发明申请公开(公告)号：US20190244337A1
公开(公告)日：2019-08-08
申请号：US16248955
申请日：2019-01-16
Applicant: NEC Laboratories America, Inc.
Inventor： Alexandru Niculescu-Mizil , Renqiang Min , Eric Cosatto , Farley Lai , Hans Peter Graf , Xavier Fontaine
CPC classification number: G08B29/186 , G06K9/4604 , G06K9/6256 , G06T3/403 , G06T7/0004 , G06T7/001 , G06T2207/20081 , G06T2207/20084
Abstract: A false alarm reduction system is provided that includes a processor cropping each input image at randomly chosen positions to form cropped images of a same size at different scales in different contexts. The system further includes a CONDA-GMM, having a first and a second conditional deep autoencoder for respectively (i) taking each cropped image without a respective center block as input for measuring a discrepancy between a reconstructed and a target center block, and (ii) taking an entirety of cropped images with the target center block. The CONDA-GMM constructs density estimates based on reconstruction error features and low-dimensional embedding representations derived from image encodings. The processor determines an anomaly existence based on a prediction of a likelihood of the anomaly existing in a framework of a CGMM, given the context being a representation of the cropped image with the center block removed and having a discrepancy above a threshold.
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224.发明授权公开(公告)号：US10340649B2
公开(公告)日：2019-07-02
申请号：US15912810
申请日：2018-03-06
Applicant: NEC LABORATORIES AMERICA, INC.
Inventor： Fatih Yaman , Shaoliang Zhang , Eduardo Mateo Rodriquez , Takanori Inoue , Yoshihisa Inada
Abstract: Aspects of the present disclosure describe systems, methods, and structures for providing C-band and L-band transmission exhibiting increased power efficiency by diverting a portion of C-band optical energy to an input of L-band optical amplifiers (C-seeding) while optionally employing circulators to eliminate the need for optical isolators.
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225.发明授权公开(公告)号：US10331974B2
公开(公告)日：2019-06-25
申请号：US15709897
申请日：2017-09-20
Applicant: NEC Laboratories America, Inc.
Inventor： Muhammad Zeeshan Zia , Quoc-Huy Tran , Xiang Yu , Manmohan Chandraker , Chi Li
IPC: G06K9/00 , G06K9/62 , G06F17/50 , G06N3/02 , G06T11/60 , G06T15/40 , G05D1/02 , G08G1/16 , G06T7/73 , G06N3/08 , G06T15/10 , B60W30/00 , G08G1/0962 , G06T7/55 , G06K9/46
Abstract: An action recognition system and method are provided. The action recognition system includes an image capture device configured to capture an actual image depicting an object. The action recognition system includes a processor configured to render, based on a set of 3D CAD models, synthetic images with corresponding intermediate shape concept labels. The processor is configured to form a multi-layer CNN which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN thereto to generate an image pair including a 2D and 3D geometric structure of the object. The processor is configured to control a device to perform a response action in response to an identification of an action performed by the object, wherein the identification of the action is based on the image pair.
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Patent Agency Ranking
公开(公告)号：US10296793B2
公开(公告)日：2019-05-21
申请号：US15479408
申请日：2017-04-05
Applicant: NEC Laboratories America, Inc.
Inventor： Renqiang Min , Yang Gao , Eric Cosatto
Abstract: A method, a computer program product, and a system are provided for video based action recognition. The system includes a processor. One or more frames from one or more video sequences are received. A feature vector for each patch of the one or more frames is generated using a deep convolutional neural network. An attention factor for the feature vectors is generated based on a within-frame attention and a between-frame attention. A target action is identified using a multi-layer deep long short-term memory process applied to the attention factor, said target action representing at least one of the one or more video sequences. An operation of a processor-based machine is controlled to change a state of the processor-based machine, responsive to the at least one of the one or more video sequences including the identified target action.
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公开(公告)号：US10290197B2
公开(公告)日：2019-05-14
申请号：US15637533
申请日：2017-06-29
Applicant: NEC Laboratories America, Inc. , NEC Hong Kong Limited
Inventor： Manmohan Chandraker , Wongun Choi , Eric Lau , Elsa Wong , Guobin Chen
Abstract: A mass transit surveillance system and corresponding method are provided. The mass transit surveillance system includes a camera configured to capture an input image of a subject purported to be a baby and presented at a mass transit environment. The mass transit surveillance system further includes a memory storing a deep learning model configured to perform a baby detection task for the mass transit environment. The mass transit surveillance system also includes a processor configured to apply the deep learning model to the input image to provide a baby detection result of either a presence or an absence of an actual baby in relation to the subject purported to be the baby. The baby detection task is configured to evaluate one or more different distractor modalities corresponding to one or more different physical spoofing materials to prevent baby spoofing for the baby detection task.
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公开(公告)号：US10289081B2
公开(公告)日：2019-05-14
申请号：US14683397
申请日：2015-04-10
Applicant: NEC Laboratories America, Inc.
Inventor： Ali Hooshmand , Ratnesh Sharma , Ceyhun Eksin
Abstract: A system to manage a power grid includes one or more storage and generator devices coupled to the power grid; and a decentralized management module to control the devices including: a module to perform decentralized local forecasts; and a module to perform decentralized device reconfiguration.
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公开(公告)号：US20190138814A1
公开(公告)日：2019-05-09
申请号：US16115630
申请日：2018-08-29
Applicant: NEC Laboratories America, Inc.
Inventor： Samuel Schulter , Wongun Choi , Tuan Hung Vu , Manmohan Chandraker
CPC classification number: G06T7/73 , G06K9/00744 , G06K9/00979 , G06K9/6232 , G06K9/629 , G06T7/20 , G06T7/269 , G06T2207/10016 , G06T2207/20016 , G06T2207/20076 , G06T2207/20081 , G06T2207/20084
Abstract: A computer-implemented method, system, and computer program product are provided for object detection utilizing an online flow guided memory network. The method includes receiving a plurality of videos, each of the plurality of videos including a plurality of frames. The method also includes generating, with a feature extraction network, a frame feature map for a current frame of the plurality of frames. The method additionally includes aggregating a memory feature map from the frame feature map and previous memory feature maps from previous frames on a plurality of time axes, with the plurality of time axes including a first time axis at a first frame increment and a second time axis at a second frame increment. The method further includes predicting, with a task network, an object from the memory feature map. The method also includes controlling an operation of a processor-based machine to react in accordance with the object.
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公开(公告)号：US20190122655A1
公开(公告)日：2019-04-25
申请号：US16163988
申请日：2018-10-18
Applicant: NEC Laboratories America, Inc.
Inventor： Renqiang Min , Dinghan Shen
Abstract: A computer-implemented method, computer program product, and computer processing system are provided for word embedding. The method includes receiving, by a processor device, a word embedding matrix. The method further includes generating, by a processor device, an average pooling vector and a max pooling vector, based on the word embedding matrix. The method also includes generating, by the processor device, a prediction by applying a Multi-Layer Perceptron (MLP) to the average pooling vector and the max pooling vector.
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