公开(公告)号：US20220114825A1

公开(公告)日：2022-04-14

申请号：US17408094

申请日：2021-08-20

Applicant: Intel Corporation

Inventor： Anbang Yao ,  Yun Ren ,  Hao Zhao ,  Tao Kong ,  Yurong Chen

IPC: G06V30/24 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: An example apparatus for mining multi-scale hard examples includes a convolutional neural network to receive a mini-batch of sample candidates and generate basic feature maps. The apparatus also includes a feature extractor and combiner to generate concatenated feature maps based on the basic feature maps and extract the concatenated feature maps for each of a plurality of received candidate boxes. The apparatus further includes a sample scorer and miner to score the candidate samples with multi-task loss scores and select candidate samples with multi-task loss scores exceeding a threshold score.

公开(公告)号：US11120314B2

公开(公告)日：2021-09-14

申请号：US16491735

申请日：2017-04-07

Applicant: INTEL CORPORATION

Inventor： Anbang Yao ,  Yun Ren ,  Hao Zhao ,  Tao Kong ,  Yurong Chen

IPC: G06K9/68 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: An example apparatus for mining multi-scale hard examples includes a convolutional neural network to receive a mini-batch of sample candidates and generate basic feature maps. The apparatus also includes a feature extractor and combiner to generate concatenated feature maps based on the basic feature maps and extract the concatenated feature maps for each of a plurality of received candidate boxes. The apparatus further includes a sample scorer and miner to score the candidate samples with multi-task loss scores and select candidate samples with multi-task loss scores exceeding a threshold score.

公开(公告)号：US11790631B2

公开(公告)日：2023-10-17

申请号：US17408094

申请日：2021-08-20

Applicant: Intel Corporation

Inventor： Anbang Yao ,  Yun Ren ,  Hao Zhao ,  Tao Kong ,  Yurong Chen

IPC: G06V10/00 ,  G06V10/44 ,  G06N3/04 ,  G06N3/08 ,  G06V30/24 ,  G06F18/243 ,  G06V30/19 ,  G06V10/82 ,  G06V20/70 ,  G06V20/10

CPC classification number: G06V10/454 ,  G06F18/24317 ,  G06N3/04 ,  G06N3/08 ,  G06V10/82 ,  G06V20/10 ,  G06V20/70 ,  G06V30/19173 ,  G06V30/2504

Abstract: An example apparatus for mining multi-scale hard examples includes a convolutional neural network to receive a mini-batch of sample candidates and generate basic feature maps. The apparatus also includes a feature extractor and combiner to generate concatenated feature maps based on the basic feature maps and extract the concatenated feature maps for each of a plurality of received candidate boxes. The apparatus further includes a sample scorer and miner to score the candidate samples with multi-task loss scores and select candidate samples with multi-task loss scores exceeding a threshold score.

公开(公告)号：US12154309B2

公开(公告)日：2024-11-26

申请号：US18462305

申请日：2023-09-06

Applicant: Intel Corporation

Inventor： Anbang Yao ,  Yun Ren ,  Hao Zhao ,  Tao Kong ,  Yurong Chen

IPC: G06V10/00 ,  G06F18/243 ,  G06N3/04 ,  G06N3/08 ,  G06V10/44 ,  G06V10/82 ,  G06V20/10 ,  G06V20/70 ,  G06V30/19 ,  G06V30/24

Abstract: An example apparatus for mining multi-scale hard examples includes a convolutional neural network to receive a mini-batch of sample candidates and generate basic feature maps. The apparatus also includes a feature extractor and combiner to generate concatenated feature maps based on the basic feature maps and extract the concatenated feature maps for each of a plurality of received candidate boxes. The apparatus further includes a sample scorer and miner to score the candidate samples with multi-task loss scores and select candidate samples with multi-task loss scores exceeding a threshold score.

公开(公告)号：US20240013506A1

公开(公告)日：2024-01-11

申请号：US18462305

申请日：2023-09-06

Applicant: Intel Corporation

Inventor： Anbang Yao ,  Yun Ren ,  Hao Zhao ,  Tao Kong ,  Yurong Chen

IPC: G06V10/44 ,  G06N3/04 ,  G06N3/08 ,  G06V30/24 ,  G06F18/243 ,  G06V30/19 ,  G06V10/82 ,  G06V20/70 ,  G06V20/10

CPC classification number: G06V10/454 ,  G06N3/04 ,  G06N3/08 ,  G06V30/2504 ,  G06F18/24317 ,  G06V30/19173 ,  G06V10/82 ,  G06V20/70 ,  G06V20/10

Abstract: An example apparatus for mining multi-scale hard examples includes a convolutional neural network to receive a mini-batch of sample candidates and generate basic feature maps. The apparatus also includes a feature extractor and combiner to generate concatenated feature maps based on the basic feature maps and extract the concatenated feature maps for each of a plurality of received candidate boxes. The apparatus further includes a sample scorer and miner to score the candidate samples with multi-task loss scores and select candidate samples with multi-task loss scores exceeding a threshold score.

公开(公告)号：US20210133518A1

公开(公告)日：2021-05-06

申请号：US16491735

申请日：2017-04-07

Applicant: INTEL CORPORATION

Inventor： Anbang Yao ,  Yun Ren ,  Hao Zhao ,  Tao Kong ,  Yurong Chen

IPC: G06K9/68 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: An example apparatus for mining multi-scale hard examples includes a convolutional neural network to receive a mini-batch of sample candidates and generate basic feature maps. The apparatus also includes a feature extractor and combiner to generate concatenated feature maps based on the basic feature maps and extract the concatenated feature maps for each of a plurality of received candidate boxes. The apparatus further includes a sample scorer and miner to score the candidate samples with multi-task loss scores and select candidate samples with multi-task loss scores exceeding a threshold score.