公开(公告)号：US11810359B2

公开(公告)日：2023-11-07

申请号：US17557933

申请日：2021-12-21

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Xin Yang ,  Xiaopeng Wei ,  Yu Qiao ,  Qiang Zhang ,  Baocai Yin ,  Haiyin Piao ,  Zhenjun Du

IPC: G06V10/00 ,  G06V20/40 ,  G06V10/46 ,  G06V10/82 ,  G06T3/40 ,  G06T7/215 ,  G06T9/00 ,  G06V10/72 ,  G06V10/764 ,  G06V10/778 ,  G06V10/774 ,  G06V10/776 ,  G06T7/10 ,  G06F18/21 ,  G06F18/214

CPC classification number: G06V20/49 ,  G06F18/217 ,  G06F18/2155 ,  G06T3/4007 ,  G06T3/4046 ,  G06T7/10 ,  G06T7/215 ,  G06T9/002 ,  G06V10/46 ,  G06V10/72 ,  G06V10/764 ,  G06V10/776 ,  G06V10/778 ,  G06V10/7753 ,  G06V10/82 ,  G06V20/41 ,  G06T2207/10016 ,  G06T2207/10024 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: The present invention belongs to the technical field of computer vision, and provides a video semantic segmentation method based on active learning, comprising an image semantic segmentation module, a data selection module based on the active learning and a label propagation module. The image semantic segmentation module is responsible for segmenting image results and extracting high-level features required by the data selection module; the data selection module selects a data subset with rich information at an image level, and selects pixel blocks to be labeled at a pixel level; and the label propagation module realizes migration from image to video tasks and completes the segmentation result of a video quickly to obtain weakly-supervised data. The present invention can rapidly generate weakly-supervised data sets, reduce the cost of manufacture of the data and optimize the performance of a semantic segmentation network.

公开(公告)号：US11361534B2

公开(公告)日：2022-06-14

申请号：US17257704

申请日：2020-03-13

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Xin Yang ,  Xiaopeng Wei ,  Qiang Zhang ,  Haiyang Mei ,  Yuanyuan Liu

IPC: G06V10/44 ,  G06V10/70 ,  G06V10/77 ,  G06V10/774 ,  G06V10/776 ,  G06V10/80

Abstract: The invention discloses a method for glass detection in a real scene, which belongs to the field of object detection. The present invention designs a combination method based on LCFI blocks to effectively integrate context features of different scales. Finally, multiple LCFI combination blocks are embedded into the glass detection network GDNet to obtain large-scale context features of different levels, thereby realize reliable and accurate glass detection in various scenarios. The glass detection network GDNet in the present invention can effectively predict the true area of glass in different scenes through this method of fusing context features of different scales, successfully detect glass with different sizes, and effectively handle with glass in different scenes. GDNet has strong adaptability to the various glass area sizes of the images in the glass detection dataset, and has the highest accuracy in the field of the same type of object detection.

公开(公告)号：US11195044B2

公开(公告)日：2021-12-07

申请号：US16963140

申请日：2020-05-13

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Xin Yang ,  Xiaopeng Wei ,  Qiang Zhang ,  Yuhao Liu ,  Yu Qiao

IPC: G06K9/46 ,  G06K9/62 ,  G06T7/11 ,  G06T7/194

Abstract: The invention belongs to the field of computer vision technology, and provides a fully automatic natural image matting method. For image matting of a single image, it is mainly composed of the extraction of high-level semantic features and low-level structural features, the filtering of pyramid features, the extraction of spatial structure information, and the late optimization of the discriminator network. The invention can generate accurate alpha matte without any auxiliary information, saving the time for scientific researchers to mark auxiliary information and the interaction time when users use it.

公开(公告)号：US11756204B2

公开(公告)日：2023-09-12

申请号：US17336702

申请日：2021-06-02

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Wen Dong ,  Xin Yang ,  Haiyang Mei ,  Xiaopeng Wei ,  Qiang Zhang

IPC: G06T7/11 ,  G06T7/73 ,  G06T7/174 ,  G06N3/08

CPC classification number: G06T7/11 ,  G06N3/08 ,  G06T7/174 ,  G06T7/74 ,  G06T2207/10024 ,  G06T2207/10028 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20221

Abstract: The invention belongs to scene segmentation's field in computer vision and is a depth-aware method for mirror segmentation. PDNet successively includes a multi-layer feature extractor, a positioning module, and a delineating module. The multi-layer feature extractor uses a traditional feature extraction network to obtain contextual features; the positioning module combines RGB feature information with depth feature information to initially determine the position of the mirror in the image; the delineating module is based on the image RGB feature information, combined with depth information to adjust and determine the boundary of the mirror. This method is the first method that uses both RGB image and depth image to achieve mirror segmentation in an image. The present invention has also been further tested. For mirrors with a large area in a complex environment, the PDNet segmentation results are still excellent, and the results at the boundary of the mirrors are also satisfactory.

公开(公告)号：US12118096B2

公开(公告)日：2024-10-15

申请号：US17948648

申请日：2022-09-20

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Qiang Zhang ,  Bin Wang ,  Pengfei Wang ,  Yuandi Shi ,  Rongrong Chen ,  Xiaopeng Wei

IPC: G06F17/16 ,  G06F21/60 ,  G06N7/01

CPC classification number: G06F21/602 ,  G06F17/16 ,  G06N7/01

Abstract: The present disclosure discloses an image encryption method based on multi-scale compressed sensing and a Markov model. According to the difference in information carried by low-frequency coefficients and high-frequency coefficients of an image, different sampling rates are set for the low-frequency coefficients and the high-frequency coefficients of the image, which can effectively improve the reconstruction quality of a decrypted image. The decrypted image obtained by the present disclosure has higher quality than the decrypted image generated by the existing scheme, and a better visual effect and more complete original image information can be obtained.

公开(公告)号：US10563569B2

公开(公告)日：2020-02-18

申请号：US15865296

申请日：2018-01-09

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Wuqiang Long ,  Hua Tian ,  Jiangping Tian ,  Yao Fu ,  Jingchen Cui ,  Kai Sheng ,  Ping Yi ,  Kunpeng Qi ,  Qiang Zhang ,  Yicong Wang

IPC: F02B23/06 ,  F02F1/24 ,  F02F3/28 ,  F02B1/12

Abstract: A diesel combustion system including a piston, an annular impinging block, and a combustion chamber. The combustion chamber is divided by the annular impinging block into an upper chamber and a lower chamber. The annular impinging block includes a lower guide surface that is adjacent to the lower chamber and that extends from a trough line connected to the piston to a crest line. The ratios among the inner diameter of the top of the piston, the outer diameter of the top of the piston, the diameter of the trough line, and the diameter of the crest line define the shape of the combustion chamber which leads to increased rate of combustion, reduced soot emission, and increased fuel efficiency.