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公开(公告)号：US10726302B2
公开(公告)日：2020-07-28
申请号：US16204242
申请日：2018-11-29
Applicant: QUALCOMM Incorporated
Inventor： Shuai Zhang , Ying Chen , Yang Zhou
IPC: G06K9/62
Abstract: Methods, systems, and devices for object localization and classification are described. A device may configure a first unit of a detection layer associated with a learning framework when a quantity of output feature channels of an input feature maps is less than or equal to a quantity of input feature channels of the input feature maps. The first set of layers may include a group convolution layer, a pointwise layer, a batch normalization layer, or a rectified linear layer, or a combination thereof. The device may also configure, a second unit of the detection layer associated with the learning framework, when a second quantity of output feature channels of the input feature maps is less than or equal to a second quantity of input feature channels of the input feature maps. The second set of layers may include a depthwise layer or a pointwise layer, or both.
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公开(公告)号：US20200175334A1
公开(公告)日：2020-06-04
申请号：US16204242
申请日：2018-11-29
Applicant: QUALCOMM Incorporated
Inventor： Shuai Zhang , Ying Chen , Yang Zhou
IPC: G06K9/62
Abstract: Methods, systems, and devices for object localization and classification are described. A device may configure a first unit of a detection layer associated with a learning framework when a quantity of output feature channels of an input feature maps is less than or equal to a quantity of input feature channels of the input feature maps. The first set of layers may include a group convolution layer, a pointwise layer, a batch normalization layer, or a rectified linear layer, or a combination thereof. The device may also configure, a second unit of the detection layer associated with the learning framework, when a second quantity of output feature channels of the input feature maps is less than or equal to a second quantity of input feature channels of the input feature maps. The second set of layers may include a depthwise layer or a pointwise layer, or both.
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公开(公告)号：US11227156B2
公开(公告)日：2022-01-18
申请号：US16239352
申请日：2019-01-03
Applicant: QUALCOMM Incorporated
Inventor： Eyasu Zemene Mequanint , Shuai Zhang , Yingyong Qi , Ning Bi
Abstract: Methods, systems, and devices for personalized (e.g., user specific) eye openness estimation are described. A network model (e.g., a convolutional neural network) may be trained using a set of synthetic eye openness image data (e.g., synthetic face images with known degrees or percentages of eye openness) and a set of real eye openness image data (e.g., facial images of real persons that are annotated as either open eyed or closed eyed). A device may estimate, using the network model, a multi-stage eye openness level (e.g., a percentage or degree to which an eye is open) of a user based on captured real time eye openness image data. The degree of eye openness estimated by the network model may then be compared to an eye size of the user (e.g., a user specific maximum eye size), and a user specific eye openness level may be estimated based on the comparison.
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Patent Agency Ranking
公开(公告)号：US11216541B2
公开(公告)日：2022-01-04
申请号：US16125360
申请日：2018-09-07
Applicant: QUALCOMM Incorporated
Inventor： Eyasu Zemene Mequanint , Shuai Zhang , Yingyong Qi , Ning Bi
Abstract: Techniques and systems are provided for authenticating a user of a device. For example, input biometric data associated with a person can be obtained. A similarity score for the input biometric data can be determined by comparing the input biometric data to a set of templates that include reference biometric data associated with the user. The similarity score can be compared to an authentication threshold. The person is authenticated as the user when the similarity score is greater than the authentication threshold. The similarity score can also be compared to a learning threshold that is greater than the authentication threshold. A new template including features of the input biometric data is saved for the user when the similarity score is less than the learning threshold and greater than the authentication threshold.
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公开(公告)号：US12141981B2
公开(公告)日：2024-11-12
申请号：US17669040
申请日：2022-02-10
Applicant: QUALCOMM Incorporated
Inventor： Shuai Zhang , Xiaowen Ying , Jiancheng Lyu , Yingyong Qi
Abstract: Systems and techniques are provided for performing semantic image segmentation using a machine learning system (e.g., including one or more cross-attention transformer layers). For instance, a process can include generating one or more input image features for a frame of image data and generating one or more input depth features for a frame of depth data. One or more fused image features can be determined, at least in part, by fusing the one or more input depth features with the one or more input image features, using a first cross-attention transformer network. One or more segmentation masks can be generated for the frame of image data based on the one or more fused image features.
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公开(公告)号：US20200218878A1
公开(公告)日：2020-07-09
申请号：US16239352
申请日：2019-01-03
Applicant: QUALCOMM Incorporated
Inventor： Eyasu Zemene Mequanint , Shuai Zhang , Yingyong Qi , Ning Bi
IPC: G06K9/00 , A61B5/11 , A61B5/1171 , G08B21/18 , G06F21/32
Abstract: Methods, systems, and devices for personalized (e.g., user specific) eye openness estimation are described. A network model (e.g., a convolutional neural network) may be trained using a set of synthetic eye openness image data (e.g., synthetic face images with known degrees or percentages of eye openness) and a set of real eye openness image data (e.g., facial images of real persons that are annotated as either open eyed or closed eyed). A device may estimate, using the network model, a multi-stage eye openness level (e.g., a percentage or degree to which an eye is open) of a user based on captured real time eye openness image data. The degree of eye openness estimated by the network model may then be compared to an eye size of the user (e.g., a user specific maximum eye size), and a user specific eye openness level may be estimated based on the comparison.
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公开(公告)号：US12236614B2
公开(公告)日：2025-02-25
申请号：US17828962
申请日：2022-05-31
Applicant: QUALCOMM Incorporated
Inventor： Jiancheng Lyu , Dashan Gao , Yingyong Qi , Shuai Zhang , Ning Bi
Abstract: Systems and techniques are provided for performing scene segmentation and object tracking. For example, a method for processing one or more frames. The method may include determining first one or more features from a first frame. The first frame includes a target object. The method may include obtaining a first mask associated with the first frame. The first mask includes an indication of the target object. The method may further include generating, based on the first mask and the first one or more features, a representation of a foreground and a background of the first frame. The method may include determining second one or more features from a second frame and determining, based on the representation of the foreground and the background of the first frame and the second one or more features, a location of the target object in the second frame.
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公开(公告)号：US11887404B2
公开(公告)日：2024-01-30
申请号：US17457365
申请日：2021-12-02
Applicant: QUALCOMM Incorporated
Inventor： Eyasu Zemene Mequanint , Shuai Zhang , Yingyong Qi , Ning Bi
CPC classification number: G06V40/172 , G06F21/32 , G06F21/44 , G06V10/17 , G06V40/50
Abstract: Techniques and systems are provided for authenticating a user of a device. For example, input biometric data associated with a person can be obtained. A similarity score for the input biometric data can be determined by comparing the input biometric data to a set of templates that include reference biometric data associated with the user. The similarity score can be compared to an authentication threshold. The person is authenticated as the user when the similarity score is greater than the authentication threshold. The similarity score can also be compared to a learning threshold that is greater than the authentication threshold. A new template including features of the input biometric data is saved for the user when the similarity score is less than the learning threshold and greater than the authentication threshold.
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