公开(公告)号：US11928753B2

公开(公告)日：2024-03-12

申请号：US16773715

申请日：2020-01-27

Applicant: INTEL CORPORATION

Inventor： Anthony Rhodes ,  Manan Goel

IPC: G06T1/20 ,  G06F18/241 ,  G06T3/40 ,  G06T7/11 ,  G06T7/174 ,  G06T9/00 ,  G06V10/26 ,  G06V10/764 ,  G06V20/40

CPC classification number: G06T1/20 ,  G06F18/241 ,  G06T3/4046 ,  G06T7/11 ,  G06T7/174 ,  G06T9/002 ,  G06V10/26 ,  G06V10/764 ,  G06V20/46 ,  G06V20/49 ,  G06T2207/10016 ,  G06T2207/20221

Abstract: Techniques related to automatically segmenting video frames into per pixel fidelity object of interest and background regions are discussed. Such techniques include applying tessellation to a video frame to generate feature frames corresponding to the video frame and applying a segmentation network implementing context aware skip connections to an input volume including the feature frames and a context feature volume corresponding to the video frame to generate a segmentation for the video frame.

公开(公告)号：US20230306603A1

公开(公告)日：2023-09-28

申请号：US18131650

申请日：2023-04-06

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Manan Goel

IPC: G06T7/11 ,  G06T7/20 ,  G06T7/174 ,  G06T7/00 ,  G06T7/70 ,  G06V20/40 ,  G06F18/24 ,  G06F18/21 ,  G06V10/764 ,  G06V10/82 ,  G06V10/44

CPC classification number: G06T7/11 ,  G06F18/217 ,  G06F18/24 ,  G06T7/174 ,  G06T7/20 ,  G06T7/70 ,  G06T7/97 ,  G06V10/454 ,  G06V10/764 ,  G06V10/82 ,  G06V20/41 ,  G06V20/49 ,  G06T2200/24 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Techniques related to automatically segmenting video frames into per pixel dense object of interest and background regions are discussed. Such techniques include applying a segmentation convolutional neural network (CNN) to a CNN input including a current video frame, a previous video frame, an object of interest indicator frame, a motion frame, and multiple feature frames each including features compressed from feature layers of an object classification convolutional neural network as applied to the current video frame to generate candidate segmentations and selecting one of the candidate segmentations as a final segmentation of the current video frame.

公开(公告)号：US11676278B2

公开(公告)日：2023-06-13

申请号：US16584709

申请日：2019-09-26

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Manan Goel

IPC: G06K9/00 ,  G06T7/11 ,  G06T7/20 ,  G06T7/174 ,  G06T7/00 ,  G06T7/70 ,  G06V20/40 ,  G06F18/24 ,  G06F18/21 ,  G06V10/764 ,  G06V10/82 ,  G06V10/44

CPC classification number: G06T7/11 ,  G06F18/217 ,  G06F18/24 ,  G06T7/174 ,  G06T7/20 ,  G06T7/70 ,  G06T7/97 ,  G06V10/454 ,  G06V10/764 ,  G06V10/82 ,  G06V20/41 ,  G06V20/49 ,  G06T2200/24 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Techniques related to automatically segmenting video frames into per pixel dense object of interest and background regions are discussed. Such techniques include applying a segmentation convolutional neural network (CNN) to a CNN input including a current video frame, a previous video frame, an object of interest indicator frame, a motion frame, and multiple feature frames each including features compressed from feature layers of an object classification convolutional neural network as applied to the current video frame to generate candidate segmentations and selecting one of the candidate segmentations as a final segmentation of the current video frame.

公开(公告)号：US20230024803A1

公开(公告)日：2023-01-26

申请号：US17936941

申请日：2022-09-30

Applicant: Intel Corporation

Inventor： Sovan Biswas ,  Anthony Rhodes ,  Ramesh Manuvinakurike ,  Giuseppe Raffa ,  Richard Beckwith

IPC: G06V20/40 ,  G06V20/70 ,  G06V10/776 ,  G06V10/774 ,  G06V10/94

Abstract: Systems, apparatuses, and methods include technology that generates final frame predictions for a first plurality of frames of a video, where the first plurality of frames is associated with unlabeled data. The technology predicts an ordered list of actions for the first plurality of frames based on the final frame predictions, and temporally aligning the ordered list of actions to the final frame predictions to generate labels.

公开(公告)号：US20210118146A1

公开(公告)日：2021-04-22

申请号：US17132810

申请日：2020-12-23

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Ke Ding ,  Manan Goel

IPC: G06T7/12 ,  G06T7/33

Abstract: Methods, systems, and apparatus for high-fidelity vision tasks using deep neural networks are disclosed. An example apparatus includes a feature extractor to extract low-level features and edge-enhanced features of an input image processed using a convolutional neural network, an eidetic memory block generator to generate an eidetic memory block using the extracted low-level features or the extracted edge-enhanced features, and an interactive segmentation network to perform image segmentation using the eidetic memory block, the eidetic memory block used to propagate domain-persistent features through the segmentation network.

公开(公告)号：US20210117841A1

公开(公告)日：2021-04-22

申请号：US17132879

申请日：2020-12-23

Applicant: Intel Corporation

Inventor： Anthony Rhodes

IPC: G06N7/00 ,  G06N20/00 ,  G06F17/18

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to improve automated machine learning. An example apparatus includes a communication processor to obtain, from a training controller, a truncated learning curve for a candidate hyperparameter configuration; an explicit mean function (EMF) generator to fit parameters of an EMF to the truncated learning curve, the EMF tailored to extrapolating learning curves for machine learning models; and an extrapolation controller to extrapolate remaining datapoints of the truncated learning curve according to the EMF to generate an extrapolated learning curve for the candidate hyperparameter configuration.

公开(公告)号：US20210110198A1

公开(公告)日：2021-04-15

申请号：US17131525

申请日：2020-12-22

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Manan Goel ,  Ke Ding

IPC: G06K9/62 ,  G06T7/10 ,  G06N3/04

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for interactive image segmentation. An example apparatus includes an inception controller to execute an inception sublayer of a convolutional neural network (CNN) including two or more inception-atrous-collation (IAC) layers, the inception sublayer including two or more convolutions including respective kernels of varying sizes to generate multi-scale inception features, the inception sublayer to receive one or more context features indicative of user input; an atrous controller to execute an atrous sublayer of the CNN, the atrous sublayer including two or more atrous convolutions including respective kernels of varying sizes to generate multi-scale atrous features; and a collation controller to execute a collation sublayer of the CNN to collate the multi-scale inception features, the multi-scale atrous features, and eidetic memory features.

公开(公告)号：US20190043520A1

公开(公告)日：2019-02-07

申请号：US15941150

申请日：2018-03-30

Applicant: Intel Corporation

Inventor： Swarnendu Kar ,  Anthony Rhodes

IPC: G10L21/0232 ,  H04R1/40 ,  G10L21/0272 ,  H04R3/00

Abstract: A mechanism is described for facilitating wind detection and wind noise reduction in computing environments according to one embodiment. An apparatus of embodiments, as described herein, includes wind detection logic to detect wind associated with the apparatus including a wearable computing device, wherein the wind is detected based on samples from multiple microphones and extraction and use of multiple features including spectral sub-band centroid (SSC) features and coherence features; and decision and execution logic to reduce wind noise associated with the detected wind.