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公开(公告)号：US10755198B2
公开(公告)日：2020-08-25
申请号：US15394711
申请日：2016-12-29
Applicant: Intel Corporation
Inventor： Darshan Iyer , Nilesh K. Jain
Abstract: Methods, apparatus, and system determine if a data class in a plurality of data classes is separable, such as by determining an average intra-class similarity within each data class, inter-class similarity across all data classes in the plurality of data classes, and determining separability based on the average intra-class similarity relative to the inter-class similarity. Data classes determined to be highly variable may be removed. Pair(s) of data classes not separable from one another may be combined into one class or one of the data classes may be dropped. A hardware accelerator, which may comprise artificial neurons, accelerate performance of the data analysis.
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公开(公告)号：US10747327B2
公开(公告)日：2020-08-18
申请号：US15195604
申请日：2016-06-28
Applicant: Intel Corporation
Inventor： Darshan Iyer , Nilesh K. Jain , Zhiqiang Liang
IPC: G06F3/0346 , G06F3/01 , G06K9/00 , G06K9/62
Abstract: Technologies for gesture recognition using downsampling are disclosed. A gesture recognition device may capture gesture data from a gesture measurement device, and downsample the captured data to a predefined number of data points. The gesture recognition device may then perform gesture recognition on the downsampled gesture data to recognize a gesture, and then perform an action based on the recognized gesture. The number of data points to which to downsample may be determined by downsampling to several different numbers of data points and comparing the performance of a gesture recognition algorithm performed on the downsampled gesture data for each different number of data points.
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公开(公告)号：US10282641B2
公开(公告)日：2019-05-07
申请号：US15200069
申请日：2016-07-01
Applicant: Intel Corporation
Inventor： Nilesh K. Jain , Soonam Lee
Abstract: Technologies for classification using sparse coding are disclosed. A compute device may include a pattern-matching accelerator, which may be able to determine the distance between an input vector (such as an image) and several basis vectors of an overcomplete dictionary stored in the pattern-matching accelerator. The pattern matching accelerator may be able to determine each of the distances simultaneously and in a fixed amount of time (i.e., with no dependence on the number of basis vectors to which the input vector is being compared). The pattern-matching accelerator may be used to determine a set of sparse coding coefficients corresponding to a subset of the overcomplete basis vectors. The sparse coding coefficients can then be used to classify the input vector.
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Patent Agency Ranking
公开(公告)号：US20180005086A1
公开(公告)日：2018-01-04
申请号：US15200069
申请日：2016-07-01
Applicant: Intel Corporation
Inventor： Nilesh K. Jain , Soonam Lee
CPC classification number: G06K9/6269 , G06K9/481 , G06K9/6249 , G06K9/6255 , G06K9/6256 , G06K2009/4695
Abstract: Technologies for classification using sparse coding are disclosed. A compute device may include a pattern-matching accelerator, which may be able to determine the distance between an input vector (such as an image) and several basis vectors of an overcomplete dictionary stored in the pattern-matching accelerator. The pattern matching accelerator may be able to determine each of the distances simultaneously and in a fixed amount of time (i.e., with no dependence on the number of basis vectors to which the input vector is being compared). The pattern-matching accelerator may be used to determine a set of sparse coding coefficients corresponding to a subset of the overcomplete basis vectors. The sparse coding coefficients can then be used to classify the input vector.
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公开(公告)号：US11449803B2
公开(公告)日：2022-09-20
申请号：US16992008
申请日：2020-08-12
Applicant: Intel Corporation
Inventor： Darshan Iyer , Nilesh K. Jain
Abstract: Methods, apparatus, and system determine if a data class in a plurality of data classes is separable, such as by determining an average intra-class similarity within each data class, inter-class similarity across all data classes in the plurality of data classes, and determining separability based on the average intra-class similarity relative to the inter-class similarity. Data classes determined to be highly variable may be removed. Pair(s) of data classes not separable from one another may be combined into one class or one of the data classes may be dropped. A hardware accelerator, which may comprise artificial neurons, accelerate performance of the data analysis.
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公开(公告)号：US11216749B2
公开(公告)日：2022-01-04
申请号：US16513800
申请日：2019-07-17
Applicant: Intel Corporation
Inventor： Luis S. Kida , Nilesh K. Jain , Darshan Iyer , Ebrahim Al Safadi
IPC: G06N20/00
Abstract: Technologies for platform-targeted machine learning include a computing device to generate a machine learning algorithm model indicative of a plurality of classes between which a user input is to be classified and translate the machine learning algorithm model into hardware code for execution on the target platform. The user input is to be classified as being associated with a particular class based on an application of one or more features to the user input, and each of the one or more features has an associated implementation cost indicative of a cost to perform on a target platform on which the corresponding feature is to be applied to the user input.
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公开(公告)号：US20210201200A1
公开(公告)日：2021-07-01
申请号：US16992008
申请日：2020-08-12
Applicant: Intel Corporation
Inventor： Darshan Iyer , Nilesh K. Jain
Abstract: Methods, apparatus, and system determine if a data class in a plurality of data classes is separable, such as by determining an average intra-class similarity within each data class, inter-class similarity across all data classes in the plurality of data classes, and determining separability based on the average intra-class similarity relative to the inter-class similarity. Data classes determined to be highly variable may be removed. Pair(s) of data classes not separable from one another may be combined into one class or one of the data classes may be dropped. A hardware accelerator, which may comprise artificial neurons, accelerate performance of the data analysis.
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公开(公告)号：US20180189376A1
公开(公告)日：2018-07-05
申请号：US15394711
申请日：2016-12-29
Applicant: Intel Corporation
Inventor： Darshan Iyer , Nilesh K. Jain
Abstract: Methods, apparatus, and system determine if a data class in a plurality of data classes is separable, such as by determining an average intra-class similarity within each data class, inter-class similarity across all data classes in the plurality of data classes, and determining separability based on the average intra-class similarity relative to the inter-class similarity. Data classes determined to be highly variable may be removed. Pair(s) of data classes not separable from one another may be combined into one class or one of the data classes may be dropped. A hardware accelerator, which may comprise artificial neurons, accelerate performance of the data analysis.
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