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公开(公告)号：US11442986B2
公开(公告)日：2022-09-13
申请号：US16792208
申请日：2020-02-15
Applicant: International Business Machines Corporation
Inventor： Chuang Gan , Sijia Liu , Subhro Das , Dakuo Wang , Yang Zhang
Abstract: Method and apparatus that includes receiving a query describing an aspect in a video, the video including a plurality of frames, identifying multiple proposals that potentially correspond to the query where each of the proposals includes a subset of the plurality of frames, ranking the proposals using a graph convolution network that identifies relationships between the proposals, and selecting, based on the ranking, one of the proposals as a video segment that correlates to the query.
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公开(公告)号：US20220253714A1
公开(公告)日：2022-08-11
申请号：US17157077
申请日：2021-01-25
Inventor： Pin-Yu Chen , Chia-Yi Hsu , Songtao Lu , Sijia Liu , Chuang Gan , Chia-Mu Yu
Abstract: A trained machine learning model and a training dataset used to train the trained machine learning model can be received. Based on the training dataset, unsupervised adversarial examples can be generated. Robustness of the trained machine learning model can be determined using the generated unsupervised adversarial examples. The training dataset can be augmented with the generated unsupervised adversarial examples. The trained machine learning model can be retrained using the augmented training dataset.
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公开(公告)号：US11348336B2
公开(公告)日：2022-05-31
申请号：US15931075
申请日：2020-05-13
Applicant: International Business Machines Corporation
Inventor： Quanfu Fan , Richard Chen , Sijia Liu , Hildegard Kuehne
Abstract: Systems and methods for performing video understanding and analysis. Sets of feature maps for high resolution images and low resolution images in a time sequence of images are combined into combined sets of feature maps each having N feature maps. A time sequence of temporally aggregated sets of feature maps is created for each combined set of feature maps by: selecting a selected combined set of feature maps corresponding to an image at time “t” in the time sequence of images; applying, by channel-wise multiplication, a feature map weighting vector to a number of combined sets of feature maps that are temporally adjacent to the selected combined set of feature maps; and summing elements of the number of combined set of feature maps into a temporally aggregated set of feature maps. The time sequence of temporally aggregated sets of feature maps is processed to perform video understanding processing.
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公开(公告)号：US11257222B2
公开(公告)日：2022-02-22
申请号：US16292847
申请日：2019-03-05
Applicant: International Business Machines Corporation
Inventor： Chuang Gan , Yang Zhang , Sijia Liu , Dakuo Wang
Abstract: Embodiments of the present invention are directed to a computer-implemented method for action localization. A non-limiting example of the computer-implemented method includes receiving, by a processor, a video and segmenting, by the processor, the video into a set of video segments. The computer-implemented method classifies, by the processor, each video segment into a class and calculates, by the processor, importance scores for each video segment of a class within the set of video segments. The computer-implemented method determines, by the processor, a winning video segment of the class within the set of video segments based on the importance scores for each video segment within the class, stores, by the processor, the winning video segment from the set of video segments, and removes the winning video segment from the set of video segments.
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25.发明授权公开(公告)号：US11227215B2
公开(公告)日：2022-01-18
申请号：US16296897
申请日：2019-03-08
Applicant: International Business Machines Corporation
Inventor： Sijia Liu , Quanfu Fan , Chuang Gan , Dakuo Wang
Abstract: Mechanisms are provided for generating an adversarial perturbation attack sensitivity (APAS) visualization. The mechanisms receive a natural input dataset and a corresponding adversarial attack input dataset, where the adversarial attack input dataset comprises perturbations intended to cause a misclassification by a computer model. The mechanisms determine a sensitivity measure of the computer model to the perturbations in the adversarial attack input dataset based on a processing of the natural input dataset and corresponding adversarial attack input dataset by the computer model. The mechanisms generate a classification activation map (CAM) for the computer model based on results of the processing and a sensitivity overlay based on the sensitivity measure. The sensitivity overlay graphically represents different classifications of perturbation sensitivities. The mechanisms apply the sensitivity overlay to the CAM to generate and output a graphical visualization output of the computer model sensitivity to perturbations of adversarial attacks.
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Patent Agency Ranking
公开(公告)号：US20210035599A1
公开(公告)日：2021-02-04
申请号：US16526990
申请日：2019-07-30
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Yang Zhang , Chuang Gan , Sijia Liu , Dakuo Wang
IPC: G10L25/57 , G10L25/30 , H04N21/845 , H04N21/81 , G06N3/04
Abstract: A computing device receives a video feed. The video feed is divided into a sequence of video segments. For each video segment, visual features of the video segment are extracted. A predicted spectrogram is generated based on the extracted visual features. A synthetic audio waveform is generated from the predicted spectrogram. All synthetic audio waveforms of the video feed are concatenated to generate a synthetic soundtrack that is synchronized with the video feed.
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公开(公告)号：US20200279155A1
公开(公告)日：2020-09-03
申请号：US16288975
申请日：2019-02-28
Applicant: International Business Machines Corporation
Inventor： Sijia Liu , Pin-Yu Chen , Chuang Gan , Lisa Amini
Abstract: A black box optimization method, system, and computer program product include implementing an average gradient estimator using a forward difference of function values at multiple random directions, performing variance reduction via gradient blending with an output of the average gradient estimator using a control variate, and performing binary quantization of a result of the variance reduction.
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28.发明申请公开(公告)号：US20200242252A1
公开(公告)日：2020-07-30
申请号：US16256267
申请日：2019-01-24
Inventor： Pin-Yu Chen , Sijia Liu , Akhilan Boopathy , Tsui-Wei Weng , Luca Daniel
Abstract: A certification method, system, and computer program product include certifying an adversarial robustness of a convolutional neural network by deriving an analytic solution for a neural network output using an efficient upper bound and an efficient lower bound on an activation function and applying the analytic solution in computing a certified robustness.
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公开(公告)号：US20200242250A1
公开(公告)日：2020-07-30
申请号：US16256107
申请日：2019-01-24
Applicant: International Business Machines Corporation
Inventor： Pin-Yu Chen , Sijia Liu , Lingfei Wu , Chia-Yu Chen
Abstract: An adversarial robustness testing method, system, and computer program product include testing a robustness of a black-box system under different access settings via an accelerator.
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公开(公告)号：US12182274B2
公开(公告)日：2024-12-31
申请号：US18382107
申请日：2023-10-20
Applicant: International Business Machines Corporation
Inventor： Pin-Yu Chen , Sijia Liu , Lingfei Wu , Chia-Yu Chen
IPC: G06F21/57 , G06N3/04 , G06N3/08 , G06V10/764 , G06V10/82
Abstract: An adversarial robustness testing method, system, and computer program product include testing, via an accelerator, a robustness of a black-box system under different access settings, where the testing includes tearing down the robustness testing to a subtask of a predetermined size.
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