Title:
完全教師あり学習用のデータセットの形成
Document Type and Number:
Japanese Patent JP7128022
Kind Code:
B2
Abstract:
The invention notably relates to a computer-implemented method of signal processing comprising providing images; for each respective one of at least a subset of the images: applying a weakly-supervised learnt function, the weakly-supervised learnt function outputting respective couples each including a respective localization and one or more respective confidence scores, each confidence score representing a probability of instantiation of a respective object category at the respective localization; determining, based on the output of the weakly-supervised learnt function, one or more respective annotations, each annotation including a respective localization and a respective label representing instantiation a respective object category at the respective localization; and forming a dataset including pieces of data, each piece of data including a respective image of the subset and at least a part of the one or more annotations determined for the respective image. Such a method improves the field of object detection.
Inventors:
Louis Dupont de Dinechan
Asma Rejeb Sfarsfar
Asma Rejeb Sfarsfar
Application Number:
JP2018088031A
Publication Date:
August 30, 2022
Filing Date:
May 01, 2018
Export Citation:
Assignee:
DASSAULT SYSTEMES
International Classes:
G06T7/00
Domestic Patent References:
| JP2008234627A | ||||
| JP2017510792A |
Other References:
Bolei Zhou et. al.,Learning Deep Features for Discriminative Localization,2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),米国,IEEE,2016年06月30日,P.2921 - 2929,https://ieeexplore.ieee.org/document/7780688
下田 和,完全教師あり学習手法を用いた弱教師あり領域分割におけるシード領域生成方法の改良,電子情報通信学会技術研究報告 Vol.117 No.211 IEICE Technical Report,Vol.2017-CVIM-208 No.23,日本,一般社団法人電子情報通信学会 The Institute of Electronics,Information and Communication Engineers,2017年09月08日,P.143~149
Yunchao Wei et. al.,STC: A Simple to Complex Framework for Weakly-Supervised Semantic Segmentation,arXiv,米国,IEEE,2016年12月07日,P.1-8,https://arxiv.org/abs/1509.03150
下田 和,完全教師あり学習手法を用いた弱教師あり領域分割におけるシード領域生成方法の改良,電子情報通信学会技術研究報告 Vol.117 No.211 IEICE Technical Report,Vol.2017-CVIM-208 No.23,日本,一般社団法人電子情報通信学会 The Institute of Electronics,Information and Communication Engineers,2017年09月08日,P.143~149
Yunchao Wei et. al.,STC: A Simple to Complex Framework for Weakly-Supervised Semantic Segmentation,arXiv,米国,IEEE,2016年12月07日,P.1-8,https://arxiv.org/abs/1509.03150
Attorney, Agent or Firm:
Asahi Patent Office
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