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公开(公告)号：US09678749B2
公开(公告)日：2017-06-13
申请号：US14578605
申请日：2014-12-22
Applicant: Intel Corporation
Inventor： Shaul Oron , Gilad Michael
CPC classification number: G06F9/3001 , G06F7/5306 , G06F9/30036 , G06F9/3004 , G06F9/3017 , G06F9/3822 , G06F9/3851 , G06F9/3855 , G06F9/3877 , G06F9/3887 , G06F9/455 , G06F9/4552
Abstract: A processor includes a front end including a decoder, an execution unit including a shift-sum multiplier (SSM), and a retirement unit. The decoder includes logic identify a multiplication instruction to multiply a first number and a second number. The execution unit includes logic to, based on the instruction, access a look-up table based on the second number to determine a plurality of shift parameters and one or more flag parameters. The SSM includes logic to use the shift parameters to shift the first number to determine a plurality of partial products, and the flag parameters to determine signs of the partial products. The SSM also includes logic to sum the partial products to yield a result of the multiplication instruction.
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公开(公告)号：US20170161271A1
公开(公告)日：2017-06-08
申请号：US14959304
申请日：2015-12-04
Applicant: Intel Corporation
Inventor： Hila Barel , Gilad Michael , Hadas Dahan
CPC classification number: G06F17/3025 , G06F17/30327 , G06F17/3033 , G06F17/30964 , G06N5/047 , G06N99/005 , G06T3/4015
Abstract: Techniques related to approximate nearest neighbor searching are discussed. Such techniques may include traversing an approximate nearest neighbor search tree from root node to a resultant leaf node while maintaining a priority queue of best matches, determining candidate entries for evaluation based on the resultant leaf node, and generating search results based on the priority queue and the candidate entries.
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公开(公告)号：US11880763B2
公开(公告)日：2024-01-23
申请号：US16886103
申请日：2020-05-28
Applicant: Intel Corporation
Inventor： Furkan Isikdogan , Bhavin V. Nayak , Joao Peralta Moreira , Chyuan-Tyng Wu , Gilad Michael
IPC: G06N3/08 , G06V10/70 , G06V10/764 , G06N3/063 , G06F18/214 , G06N3/048 , G06V10/774 , G06V10/776 , G06V10/82
CPC classification number: G06N3/08 , G06F18/214 , G06N3/048 , G06N3/063 , G06V10/70 , G06V10/764 , G06V10/774 , G06V10/776 , G06V10/82
Abstract: An apparatus to facilitate partially-frozen neural networks for efficient computer vision systems is disclosed. The apparatus includes a frozen core to store fixed weights of a machine learning model, one or more trainable cores coupled to the frozen core, the one or more trainable cores comprising multipliers for trainable weights of the machine learning model, and wherein the alpha blending layer includes a trainable alpha blending parameter, and wherein the trainable alpha blending parameter is a function of a trainable parameter, a sigmoid function, and outputs of frozen and trainable blocks in a preceding layer of the machine learning model.
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公开(公告)号：US11699217B2
公开(公告)日：2023-07-11
申请号：US17242849
申请日：2021-04-28
Applicant: Intel Corporation
Inventor： Furkan Isikdogan , Timo Gerasimow , Gilad Michael
IPC: G06T5/00 , G06V40/18 , G06T3/00 , G06T5/20 , G06T7/73 , G06F18/214 , G06F18/21 , G06V10/764 , G06V10/82 , G06V10/44 , G06V10/98
CPC classification number: G06T5/006 , G06F18/214 , G06F18/217 , G06T3/0093 , G06T5/20 , G06T7/73 , G06V10/454 , G06V10/764 , G06V10/82 , G06V10/98 , G06V40/193 , G06T2207/30041 , G06T2210/44
Abstract: An example apparatus for adjusting eye gaze in images one or more processors to execute instructions to bidirectionally train a neural network; access a target angle and an input image, the input image including an eye in a first position; generate a vector field with the neural network; and generate a gaze-adjusted image based on the vector field, the gaze-adjusted image including the eye in a second position.
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25.发明授权公开(公告)号：US11625559B2
公开(公告)日：2023-04-11
申请号：US16833263
申请日：2020-03-27
Applicant: Intel Corporation
Inventor： Avi Kalderon , Gilad Michael , Joao Peralta Moreira , Bhavin Nayak , Furkan Isikdogan
Abstract: An apparatus, method, and a computer readable medium for attenuating visual artifacts in processed images. An annotated dataset of images to be processed by an image processing system is created. An adversarial control network is trained to operate as an image quality expert in classifying images. After the adversarial control network has been trained, the adversarial control network is used to supervise the image processing system on-the-fly.
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Patent Agency Ranking
公开(公告)号：US20210248714A1
公开(公告)日：2021-08-12
申请号：US17242849
申请日：2021-04-28
Applicant: Intel Corporation
Inventor： Furkan Isikdogan , Timo Gerasimow , Gilad Michael
Abstract: An example apparatus for adjusting eye gaze in images one or more processors to execute instructions to bidirectionally train a neural network; access a target angle and an input image, the input image including an eye in a first position; generate a vector field with the neural network; and generate a gaze-adjusted image based on the vector field, the gaze-adjusted image including the eye in a second position.
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公开(公告)号：US11024002B2
公开(公告)日：2021-06-01
申请号：US16412994
申请日：2019-05-15
Applicant: INTEL CORPORATION
Inventor： Furkan Isikdogan , Timo Gerasimow , Gilad Michael
Abstract: An example apparatus for correcting gaze in images includes an image receiver to receive an image comprising an eye and a target angle set to a center. The apparatus also includes a bidirectionally trained convolutional neural network (CNN) to receive the image and the target angle from the image receiver and generate a vector field and a brightness map based on the image and the target angle. The apparatus further includes an image corrector to generate a gaze corrected image based on the vector field and the brightness map.
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公开(公告)号：US20210019565A1
公开(公告)日：2021-01-21
申请号：US17063414
申请日：2020-10-05
Applicant: Intel Corporation
Inventor： Aleksandar Sutic , Zoran Zivkovic , Gilad Michael
Abstract: In an example method for training image signal processors, a reconstructed image is generated via an image signal processor based on a sensor image. An intermediate loss function is generated based on a comparison of an output of one or more corresponding layers of a computer vision network and a copy of the computer vision network. The output of the computer vision network is based on the reconstructed image. An image signal processor is trained based on the intermediate loss function.
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29.发明授权公开(公告)号：US10885384B2
公开(公告)日：2021-01-05
申请号：US16232715
申请日：2018-12-26
Applicant: Intel Corporation
Inventor： Gilad Michael , Sushma Rao
Abstract: Techniques related to computer vision tasks are discussed. Such techniques include applying a pretrained non-linear transform and pretrained details boosting factor to generate an enhanced image from an input image and reducing the bit depth of the enhanced image prior to applying a pretrained computer vision network to perform the computer vision task.
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公开(公告)号：US20190266701A1
公开(公告)日：2019-08-29
申请号：US16412994
申请日：2019-05-15
Applicant: INTEL CORPORATION
Inventor： Furkan Isikdogan , Timo Gerasimow , Gilad Michael
Abstract: An example apparatus for correcting gaze in images includes an image receiver to receive an image comprising an eye and a target angle set to a center. The apparatus also includes a bidirectionally trained convolutional neural network (CNN) to receive the image and the target angle from the image receiver and generate a vector field and a brightness map based on the image and the target angle. The apparatus further includes an image corrector to generate a gaze corrected image based on the vector field and the brightness map.
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