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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：US20180268292A1
公开(公告)日：2018-09-20
申请号：US15908870
申请日：2018-03-01
Applicant: NEC Laboratories America, Inc.
Inventor： Wongun Choi , Manmohan Chandraker , Guobin Chen , Xiang Yu
CPC classification number: G06N3/08 , G06K9/00684 , G06K9/4628 , G06K9/6217 , G06K9/6264 , G06K9/6274 , G06K9/66 , G06N3/0454 , G06N3/0481 , G06N3/084
Abstract: A computer-implemented method executed by at least one processor for training fast models for real-time object detection with knowledge transfer is presented. The method includes employing a Faster Region-based Convolutional Neural Network (R-CNN) as an objection detection framework for performing the real-time object detection, inputting a plurality of images into the Faster R-CNN, and training the Faster R-CNN by learning a student model from a teacher model by employing a weighted cross-entropy loss layer for classification accounting for an imbalance between background classes and object classes, employing a boundary loss layer to enable transfer of knowledge of bounding box regression from the teacher model to the student model, and employing a confidence-weighted binary activation loss layer to train intermediate layers of the student model to achieve similar distribution of neurons as achieved by the teacher model.
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Patent Agency Ranking
公开(公告)号：US20180046646A1
公开(公告)日：2018-02-15
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
CPC classification number: G08B21/0205 , G06F17/30256 , G06F17/30259 , G06K9/00067 , G06N99/005 , G08B21/0208 , G08B21/0222 , G08B21/0461 , G08B21/24
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：US20180047272A1
公开(公告)日：2018-02-15
申请号：US15637360
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
IPC: G08B21/02
CPC classification number: G08B21/0205 , G06F17/30256 , G06F17/30259 , G06K9/00067 , G06N99/005 , G08B21/0208 , G08B21/0222 , G08B21/0461 , G08B21/24
Abstract: A baby detection system and corresponding method are provided. The baby detection system includes a camera configured to capture an input image of a subject purported to be a baby and presented at an electronic-gate system. The baby detection system further includes a memory storing a deep learning model configured to perform a baby detection task for an electronic-gate application corresponding to the electronic-gate system. The baby detection 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：US20180046645A1
公开(公告)日：2018-02-15
申请号：US15637433
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
CPC classification number: G08B21/0205 , G06F17/30256 , G06F17/30259 , G06K9/00067 , G06N99/005 , G08B21/0208 , G08B21/0222 , G08B21/0461 , G08B21/24
Abstract: A smuggling detection system and corresponding method are provided. The smuggling detection system includes a camera configured to capture an input image of a subject purported to be a baby. The smuggling detection system further includes a memory storing a deep learning model configured to perform a baby detection task for a smuggling detection application. The smuggling detection 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：US10290196B2
公开(公告)日：2019-05-14
申请号：US15637433
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 smuggling detection system and corresponding method are provided. The smuggling detection system includes a camera configured to capture an input image of a subject purported to be a baby. The smuggling detection system further includes a memory storing a deep learning model configured to perform a baby detection task for a smuggling detection application. The smuggling detection 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：US09905104B1
公开(公告)日：2018-02-27
申请号：US15637360
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
CPC classification number: G08B21/0205 , G06F17/30256 , G06F17/30259 , G06K9/00067 , G06N99/005 , G08B21/0208 , G08B21/0222 , G08B21/0461 , G08B21/24
Abstract: A baby detection system and corresponding method are provided. The baby detection system includes a camera configured to capture an input image of a subject purported to be a baby and presented at an electronic-gate system. The baby detection system further includes a memory storing a deep learning model configured to perform a baby detection task for an electronic-gate application corresponding to the electronic-gate system. The baby detection 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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