公开(公告)号：US10262410B2

公开(公告)日：2019-04-16

申请号：US15279664

申请日：2016-09-29

Applicant: NUCTECH COMPANY LIMITED

Inventor： Zhiqiang Chen ,  Li Zhang ,  Ziran Zhao ,  Yaohong Liu ,  Cun Cheng ,  Qiang Li ,  Jianping Gu ,  Jian Zhang ,  Gang Fu

IPC: G06T7/00 ,  G06K9/00 ,  G06K9/46 ,  G06Q30/00 ,  G06K9/32 ,  G06T7/11 ,  G06K9/18 ,  G06K9/62 ,  G06T7/136

Abstract: The present disclosure provides a method and a system for inspecting goods. The method includes the steps of: obtaining a transmission image and a HSCODE of inspected goods; processing the transmission image to obtain a region of interest; retrieving from a model library a model created based on the HSCODE, in accordance with the HSCODE of the inspected goods; and determining whether there are any goods not registered in a customs declaration that are contained in the region of interest based on the model. With the above solution, it is possible to inspect goods in a container efficiently, so as to find out whether there are goods not indicated in the customs declaration that are concealed in the container.

公开(公告)号：US12131543B2

公开(公告)日：2024-10-29

申请号：US17202088

申请日：2021-03-15

Applicant: Tsinghua University ,  Nuctech Company Limited

Inventor： Li Zhang ,  Zhiqiang Chen ,  Yuanjing Li ,  Yuxiang Xing ,  Fanhua Meng ,  Qiang Li ,  Wei Li ,  Gang Fu

IPC: G06F16/583 ,  G06F16/55 ,  G06V10/20 ,  G06V10/75 ,  G06V10/764 ,  G06V10/82 ,  G06V20/20 ,  G06V20/52 ,  G06Q10/0832

CPC classification number: G06V20/52 ,  G06F16/55 ,  G06F16/583 ,  G06V10/255 ,  G06V10/75 ,  G06V10/764 ,  G06V10/82 ,  G06V20/20 ,  G06Q10/0832

Abstract: A semantic-based method and apparatus for retrieving a perspective image, an electronic device and a computer-readable storage medium are provided. An method includes obtaining a perspective image for a space containing an inspected object therein. A semantic division on the perspective image is performed using a first method, to obtain a plurality of semantic region units. A feature extraction network is constructed using a second method. Based on the perspective image and each of the plurality of semantic region units, a feature of each semantic region unit is extracted using the feature extraction network. Based on the feature of each semantic region unit, an image most similar to the semantic region unit is retrieved from an image feature database, to assist in determining an inspected object in the semantic region unit.

公开(公告)号：US20210286842A1

公开(公告)日：2021-09-16

申请号：US17202088

申请日：2021-03-15

Applicant: Tsinghua University ,  Nuctech Company Limited

Inventor： Li Zhang ,  Zhiqiang Chen ,  Yuanjing Li ,  Yuxiang Xing ,  Fanhua Meng ,  Qiang Li ,  Wei Li ,  Gang Fu

IPC: G06F16/583 ,  G06K9/00 ,  G06F16/55

Abstract: A semantic-based method and apparatus for retrieving a perspective image, an electronic device and a computer-readable storage medium are provided. An method includes obtaining a perspective image for a space containing an inspected object therein. A semantic division on the perspective image is performed using a first method, to obtain a plurality of semantic region units. A feature extraction network is constructed using a second method. Based on the perspective image and each of the plurality of semantic region units, a feature of each semantic region unit is extracted using the feature extraction network. Based on the feature of each semantic region unit, an image most similar to the semantic region unit is retrieved from an image feature database, to assist in determining an inspected object in the semantic region unit.

公开(公告)号：US20180196158A1

公开(公告)日：2018-07-12

申请号：US15868378

申请日：2018-01-11

Applicant: Tsinghua University ,  Nuctech Company Limited

Inventor： Gang Fu ,  Jun Zhang ,  Jianping Gu ,  Yaohong Liu ,  Ziran Zhao

IPC: G01V5/00 ,  G06T7/00

CPC classification number: G01V5/0016 ,  G06T7/001 ,  G06T2207/10116

Abstract: An inspection device and a method for detecting a firearm are disclosed. X-ray inspection is performed on an inspected object to obtain a transmission image. A plurality of candidate regions in the transmission image are determined using a trained firearm detection neural network. The plurality of candidate regions are classified using the firearm detection neural network to determine whether there is a firearm included in the transmission image. With the above solution, it is possible to determine more accurately whether there is a firearm included in a container/vehicle.