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公开(公告)号:US11531850B2
公开(公告)日:2022-12-20
申请号:US16947590
申请日:2020-08-07
Applicant: Intel Corporation
Inventor: Yen-Kuang Chen , Shao-Wen Yang , Ibrahima J. Ndiour , Yiting Liao , Vallabhajosyula S. Somayazulu , Omesh Tickoo , Srenivas Varadarajan
IPC: G06K9/62 , G06F9/48 , G06F9/50 , G06F16/535 , G06F16/538 , G06F16/951 , G06F21/44 , G06F21/45 , G06F21/53 , G06F21/62 , G06F21/64 , H04L9/06 , G06N5/02 , G06N3/04 , H04L9/32 , H04W4/70 , G06F16/54 , G06N3/063 , G06V10/20 , G06V10/40 , G06V10/75 , G06V10/44 , G06V20/00 , G06V40/20 , G06V40/16 , H04L67/51 , G06T7/11 , G06V10/96 , G06V30/262 , G06K15/02 , G06N3/08 , H04L67/12 , H04N19/80 , H04N19/46 , G06T7/70 , H04W12/02 , H04L9/00 , H04N19/12 , H04N19/124 , H04N19/167 , H04N19/172 , H04N19/176 , H04N19/44 , H04N19/48 , H04N19/513 , G06V30/194 , G06T7/20 , H04N19/42 , H04N19/625 , H04N19/63 , G06T7/223 , H04L67/10
Abstract: In one embodiment, an apparatus comprises a storage device and a processor. The storage device may store a plurality of compressed images comprising one or more compressed master images and one or more compressed slave images. The processor may: identify an uncompressed image; access context information associated with the uncompressed image and the one or more compressed master images; determine, based on the context information, whether the uncompressed image is associated with a corresponding master image; upon a determination that the uncompressed image is associated with the corresponding master image, compress the uncompressed image into a corresponding compressed image with reference to the corresponding master image; upon a determination that the uncompressed image is not associated with the corresponding master image, compress the uncompressed image into the corresponding compressed image without reference to the one or more compressed master images; and store the corresponding compressed image on the storage device.
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公开(公告)号:US20220223035A1
公开(公告)日:2022-07-14
申请号:US17497287
申请日:2021-10-08
Applicant: Intel Corporation
Inventor: Shao-Wen Yang , Eve M. Schooler , Maruti Gupta Hyde , Hassnaa Moustafa , Katalin Klara Bartfai-Walcott , Yen-Kuang Chen , Jessica McCarthy , Christina R. Strong , Arun Raghunath , Deepak S. Vembar
IPC: G08G1/09 , G06F9/50 , G06F21/60 , G06F9/48 , G06F21/62 , G06K9/62 , G06V10/44 , G06V20/52 , G06V40/10 , G06Q50/26 , G11B27/031 , H04N7/18
Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory is to store sensor data captured by one or more sensors associated with a first device. Further, the processor comprises circuitry to: access the sensor data captured by the one or more sensors associated with the first device; determine that an incident occurred within a vicinity of the first device; identify a first collection of sensor data associated with the incident, wherein the first collection of sensor data is identified from the sensor data captured by the one or more sensors; preserve, on the memory, the first collection of sensor data associated with the incident; and notify one or more second devices of the incident, wherein the one or more second devices are located within the vicinity of the first device.
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公开(公告)号:US11368532B2
公开(公告)日:2022-06-21
申请号:US16835211
申请日:2020-03-30
Applicant: Intel Corporation
Inventor: Shao-Wen Yang , Lei Yang , Anand P. Rangarajan , Vijay Sarathi Kesavan , Xingang Guo
Abstract: A particular device is provided with a communications module to receive signals of a plurality of devices within range of the particular device and further provisioned with grouping logic. The grouping logic is executable by one or more processors to determine from each of the signals a respective identifier for each of the plurality of devices, determine, based at least in part on the identifiers, that a particular subset of the plurality of devices are also included with the particular device in a particular one of a plurality of defined groups, and converge data received from the particular subset of devices based on the particular group.
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公开(公告)号:US20220191537A1
公开(公告)日:2022-06-16
申请号:US17509246
申请日:2021-10-25
Applicant: Intel Corporation
Inventor: Yiting Liao , Yen-Kuang Chen , Shao-Wen Yang , Vallabhajosyula S. Somayazulu , Srenivas Varadarajan , Omesh Tickoo , Ibrahima J. Ndiour
IPC: H04N19/52 , H04N19/523 , G06N3/04 , G06K9/62 , H04N19/172 , G06V10/20
Abstract: In one embodiment, an apparatus comprises processing circuitry to: receive, via a communication interface, a compressed video stream captured by a camera, wherein the compressed video stream comprises: a first compressed frame; and a second compressed frame, wherein the second compressed frame is compressed based at least in part on the first compressed frame, and wherein the second compressed frame comprises a plurality of motion vectors; decompress the first compressed frame into a first decompressed frame; perform pixel-domain object detection to detect an object at a first position in the first decompressed frame; and perform compressed-domain object detection to detect the object at a second position in the second compressed frame, wherein the object is detected at the second position in the second compressed frame based on: the first position of the object in the first decompressed frame; and the plurality of motion vectors from the second compressed frame.
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公开(公告)号:US20220035678A1
公开(公告)日:2022-02-03
申请号:US17201635
申请日:2021-03-15
Applicant: Intel Corporation
Inventor: Shao-Wen Yang
Abstract: In one embodiment, an apparatus comprises a communication interface to communicate over a network, and a processor. The processor is to: receive a workload provisioning request from a user, wherein the workload provisioning request comprises information associated with a workload, a network topology, and a plurality of potential hardware choices for deploying the workload over the network topology; receive hardware performance information for the plurality of potential hardware choices from one or more hardware providers; generate a task dependency graph associated with the workload; generate a device connectivity graph associated with the network topology; select, based on the task dependency graph and the device connectivity graph, one or more hardware choices from the plurality of potential hardware choices; and provision a plurality of resources for deploying the workload over the network topology, wherein the plurality of resources are provisioned based on the one or more hardware choices.
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公开(公告)号:US20220021583A1
公开(公告)日:2022-01-20
申请号:US17306304
申请日:2021-05-03
Applicant: Intel Corporation
Inventor: Silviu Petria , Andra Paraschiv , George Cristian Dumitru Milescu , Ulf Christian Bjorkengren , Shao-Wen Yang
Abstract: A gateway is provided with configuration management logic to identify a set of configurations corresponding to a deployment of a particular application, and automatically send corresponding configuration data to a set of devices in range of the gateway. Service management logic of the gateway determines that assets on the set of devices correspond to one or more asset abstractions defined for the particular application, where the configuration data is sent to the set of devices based on the assets corresponding to the asset abstractions. Sensor data is received during the deployment as generated by a sensor asset of one of the devices, the sensor data is processed according to service logic of the particular application to generate a result, and actuating data is generated and sent during the deployment to an actuator asset on the set of devices based on the result.
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公开(公告)号:US11121949B2
公开(公告)日:2021-09-14
申请号:US16736539
申请日:2020-01-07
Applicant: Intel Corporation
Inventor: Hong-Min Chu , Shao-Wen Yang , Yen-Kuang Chen
Abstract: Example task assignment methods disclosed herein for video analytics processing in a cloud computing environment include determining a graph, such as a directed acyclic graph, including nodes and edges to represent a plurality of video sources, a cloud computing platform, and a plurality of intermediate network devices in the cloud computing environment. Disclosed example task assignment methods also include specifying task orderings for respective sequences of video analytics processing tasks to be executed in the cloud computing environment on respective video source data generated by respective ones of the video sources. Disclosed example task assignment methods further include assigning, based on the graph and the task orderings, combinations of the video sources, the intermediate network devices and the cloud computing platform to execute the respective sequences of video analytics processing tasks to reduce an overall bandwidth utilized by the sequences of video analytics processing tasks in the cloud computing environment.
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公开(公告)号:US20210272467A1
公开(公告)日:2021-09-02
申请号:US17256105
申请日:2018-09-28
Applicant: Intel Corporation
Inventor: Shao-Wen Yang , Addicam V. Sanjay , Karthik Veeramani , Gabriel L. Silva , Marcos P. Da Silva , Jose A. Avalos , Stephen T. Palermo , Glen J. Anderson , Meng Shi , Benjamin W. Bair , Pete A. Denman , Reese L. Bowes , Rebecca A. Chierichetti , Ankur Agrawal , Mrutunjayya Mrutunjayya , Gerald A. Rogers , Shih-Wei Roger Chien , Lenitra M. Durham , Giuseppe Raffa , Irene Liew , Edwin Verplanke
Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory is to store sensor data, wherein the sensor data is captured by a plurality of sensors within an educational environment. The processor is to: access the sensor data captured by the plurality of sensors; identify a student within the educational environment based on the sensor data; detect a plurality of events associated with the student based on the sensor data, wherein each event is indicative of an attention level of the student within the educational environment; generate a report based on the plurality of events associated with the student; and send the report to a third party associated with the student.
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公开(公告)号:US20210243012A1
公开(公告)日:2021-08-05
申请号:US16948304
申请日:2020-09-11
Applicant: Intel Corporation
Inventor: Yen-Kuang Chen , Shao-Wen Yang , Ibrahima J. Ndiour , Yiting Liao , Vallabhajosyula S. Somayazulu , Omesh Tickoo , Srenivas Varadarajan
IPC: H04L9/06 , G06F21/64 , G06F21/53 , G06N5/02 , G06K9/00 , G06N3/04 , H04L29/08 , G06F21/45 , H04L9/32 , H04W4/70 , G06F21/44 , G06K9/46 , G06K9/62 , G06F16/538 , G06F16/535 , G06F16/54 , G06F21/62 , G06F9/50 , G06N3/063 , G06N3/08 , H04N19/80 , G06F16/951 , G06K9/36 , H04N19/46 , G06T7/70 , G06K9/64 , G06K9/72
Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.
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公开(公告)号:US20210174155A1
公开(公告)日:2021-06-10
申请号:US16947096
申请日:2020-07-17
Applicant: Intel Corporation
Inventor: Ned M. Smith , Katalin Klara Bartfai-Walcott , Eve M. Schooler , Shao-Wen Yang
Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory stores visual data captured by one or more sensors. The processor detects one or more first objects in the visual data based on a machine learning model and one or more first reference templates. The processor further determines, based on an object ontology, that the visual data is expected to contain a second object, wherein the object ontology indicates that the second object is related to the one or more first objects. The processor further detects the second object in the visual data based on the machine learning model and a second reference template. The processor further determines, based on an inference rule, that the visual data is expected to contain a third object. The processor further detects the third object in the visual data based on the machine learning model and a third reference template.
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